00542nas a2200169 4500008004500000245006600045210006600111300001000177490000700187653002100194653000800215653000800223653003000231653001300261100002000274856007800294 2023 Engldsh 00aExpanding the Meaning of Adaptive Testing to Enhance Validity0 aExpanding the Meaning of Adaptive Testing to Enhance Validity a22-310 v1010aAdaptive Testing10aCAT10aCBT10atest-taking disengagement10avalidity1 aWise, Steven, L uhttp://mail.iacat.org/expanding-meaning-adaptive-testing-enhance-validity00733nas a2200193 4500008004500000245009100045210006900136300001000205490000700215653003500222653003400257653002900291653002600320100001900346700002700365700002400392700002100416856010200437 2023 Engldsh 00aHow Do Trait Change Patterns Affect the Performance of Adaptive Measurement of Change?0 aHow Do Trait Change Patterns Affect the Performance of Adaptive  a32-580 v1010aadaptive measurement of change10acomputerized adaptive testing10alongitudinal measurement10atrait change patterns1 aTai, Ming, Him1 aCooperman, Allison, W.1 aDeWeese, Joseph, N.1 aWeiss, David, J. uhttp://mail.iacat.org/how-do-trait-change-patterns-affect-performance-adaptive-measurement-change02111nas a2200193 4500008003900000245007100039210006900110300000900179490000700188520153100195653000701726653003201733653001701765653002301782100001501805700001501820700001901835856006301854 2020 d00aItem Calibration Methods With Multiple Subscale Multistage Testing0 aItem Calibration Methods With Multiple Subscale Multistage Testi a3-280 v573 aAbstract Many large-scale educational surveys have moved from linear form design to multistage testing (MST) design. One advantage of MST is that it can provide more accurate latent trait (θ) estimates using fewer items than required by linear tests. However, MST generates incomplete response data by design; hence, questions remain as to how to calibrate items using the incomplete data from MST design. Further complication arises when there are multiple correlated subscales per test, and when items from different subscales need to be calibrated according to their respective score reporting metric. The current calibration-per-subscale method produced biased item parameters, and there is no available method for resolving the challenge. Deriving from the missing data principle, we showed when calibrating all items together the Rubin's ignorability assumption is satisfied such that the traditional single-group calibration is sufficient. When calibrating items per subscale, we proposed a simple modification to the current calibration-per-subscale method that helps reinstate the missing-at-random assumption and therefore corrects for the estimation bias that is otherwise existent. Three mainstream calibration methods are discussed in the context of MST, they are the marginal maximum likelihood estimation, the expectation maximization method, and the fixed parameter calibration. An extensive simulation study is conducted and a real data example from NAEP is analyzed to provide convincing empirical evidence.10aEM10amarginal maximum likelihood10amissing data10amultistage testing1 aWang, Chun1 aChen, Ping1 aJiang, Shengyu uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1224101507nas a2200157 4500008003900000245011800039210006900157300001200226490000700238520096800245100001901213700002001232700002101252700001301273856006301286 2020 d00aItem Selection and Exposure Control Methods for Computerized Adaptive Testing with Multidimensional Ranking Items0 aItem Selection and Exposure Control Methods for Computerized Ada a343-3690 v573 aAbstract The use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across items). To address these issues, we introduce subpool partition strategies for item selection and within-person statement exposure control procedures. Simulations showed that the multinomial method reduces computation time while maintaining measurement precision. Both the freeze and revised Sympson-Hetter online (RSHO) methods controlled the statement exposure rate; RSHO sacrificed some measurement precision but increased pool use. Furthermore, preventing a statement's repetition on consecutive items neither hindered the effectiveness of the freeze or RSHO method nor reduced measurement precision.1 aChen, Chia-Wen1 aWang, Wen-Chung1 aChiu, Ming, Ming1 aRo, Sage uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1225200452nas a2200133 4500008004500000022001400045245007200059210006900131300000900200490000600209100002300215700002000238856006000258 2020 Engldsh  a2165-659200aThree Measures of Test Adaptation Based on Optimal Test Information0 aThree Measures of Test Adaptation Based on Optimal Test Informat a1-190 v81 aKingsbury, Gage, G1 aWise, Steven, L uhttp://iacat.org/jcat/index.php/jcat/article/view/80/3700452nas a2200133 4500008004500000022001400045245007200059210006900131300000900200490000600209100002300215700002000238856006000258 2020 Engldsh  a2165-659200aThree Measures of Test Adaptation Based on Optimal Test Information0 aThree Measures of Test Adaptation Based on Optimal Test Informat a1-190 v81 aKingsbury, Gage, G1 aWise, Steven, L uhttp://iacat.org/jcat/index.php/jcat/article/view/80/3701989nas a2200133 4500008003900000245006800039210006800107300001000175490000700185520158200192100001701774700001901791856004501810 2019 d00aAdaptive Testing With a Hierarchical Item Response Theory Model0 aAdaptive Testing With a Hierarchical Item Response Theory Model a51-670 v433 aThe hierarchical item response theory (H-IRT) model is very flexible and allows a general factor and subfactors within an overall structure of two or more levels. When an H-IRT model with a large number of dimensions is used for an adaptive test, the computational burden associated with interim scoring and selection of subsequent items is heavy. An alternative approach for any high-dimension adaptive test is to reduce dimensionality for interim scoring and item selection and then revert to full dimensionality for final score reporting, thereby significantly reducing the computational burden. This study compared the accuracy and efficiency of final scoring for multidimensional, local multidimensional, and unidimensional item selection and interim scoring methods, using both simulated and real item pools. The simulation study was conducted under 10 conditions (i.e., five test lengths and two H-IRT models) with a simulated sample of 10,000 students. The study with the real item pool was conducted using item parameters from an actual 45-item adaptive test with a simulated sample of 10,000 students. Results indicate that the theta estimations provided by the local multidimensional and unidimensional item selection and interim scoring methods were relatively as accurate as the theta estimation provided by the multidimensional item selection and interim scoring method, especially during the real item pool study. In addition, the multidimensional method required the longest computation time and the unidimensional method required the shortest computation time.1 aWang, Wenhao1 aKingston, Neal uhttps://doi.org/10.1177/014662161876571402022nas a2200193 4500008003900000245010500039210006900144300001200213490000700225520140200232100002301634700001901657700001801676700002101694700002201715700002801737700001801765856004501783 2019 d00aAn Investigation of Exposure Control Methods With Variable-Length CAT Using the Partial Credit Model0 aInvestigation of Exposure Control Methods With VariableLength CA a624-6380 v433 aThe purpose of this simulation study was to investigate the effect of several different item exposure control procedures in computerized adaptive testing (CAT) with variable-length stopping rules using the partial credit model. Previous simulation studies on CAT exposure control methods with polytomous items rarely considered variable-length tests. The four exposure control techniques examined were the randomesque with a group of three items, randomesque with a group of six items, progressive-restricted standard error (PR-SE), and no exposure control. The two variable-length stopping rules included were the SE and predicted standard error reduction (PSER), along with three item pools of varied sizes (43, 86, and 172 items). Descriptive statistics on number of nonconvergent cases, measurement precision, testing burden, item overlap, item exposure, and pool utilization were calculated. Results revealed that the PSER stopping rule administered fewer items on average while maintaining measurement precision similar to the SE stopping rule across the different item pool sizes and exposure controls. The PR-SE exposure control procedure surpassed the randomesque methods by further reducing test overlap, maintaining maximum exposure rates at the target rate or lower, and utilizing all items from the pool with a minimal increase in number of items administered and nonconvergent cases.1 aLeroux, Audrey, J.1 aWaid-Ebbs, Kay1 aWen, Pey-Shan1 aHelmer, Drew, A.1 aGraham, David, P.1 aO’Connor, Maureen, K.1 aRay, Kathleen uhttps://doi.org/10.1177/014662161882485601810nas a2200133 4500008003900000245010200039210006900141300001200210490000700222520136300229100001901592700002001611856004501631 2019 d00aMultidimensional Computerized Adaptive Testing Using Non-Compensatory Item Response Theory Models0 aMultidimensional Computerized Adaptive Testing Using NonCompensa a464-4800 v433 aCurrent use of multidimensional computerized adaptive testing (MCAT) has been developed in conjunction with compensatory multidimensional item response theory (MIRT) models rather than with non-compensatory ones. In recognition of the usefulness of MCAT and the complications associated with non-compensatory data, this study aimed to develop MCAT algorithms using non-compensatory MIRT models and to evaluate their performance. For the purpose of the study, three item selection methods were adapted and compared, namely, the Fisher information method, the mutual information method, and the Kullback–Leibler information method. The results of a series of simulations showed that the Fisher information and mutual information methods performed similarly, and both outperformed the Kullback–Leibler information method. In addition, it was found that the more stringent the termination criterion and the higher the correlation between the latent traits, the higher the resulting measurement precision and test reliability. Test reliability was very similar across the dimensions, regardless of the correlation between the latent traits and termination criterion. On average, the difficulties of the administered items were found to be at a lower level than the examinees’ abilities, which shed light on item bank construction for non-compensatory items.1 aHsu, Chia-Ling1 aWang, Wen-Chung uhttps://doi.org/10.1177/014662161880028001609nas a2200205 4500008004500000022001400045245005000059210004900109300001000158490000600168520099300174653003501167653003401202653002301236653001901259653002701278100002301305700001501328856006001343 2019 Engldsh  a2165-659200aTime-Efficient Adaptive Measurement of Change0 aTimeEfficient Adaptive Measurement of Change a15-340 v73 a

The adaptive measurement of change (AMC) refers to the use of computerized adaptive testing (CAT) at multiple occasions to efficiently assess a respondent’s improvement, decline, or sameness from occasion to occasion. Whereas previous AMC research focused on administering the most informative item to a respondent at each stage of testing, the current research proposes the use of Fisher information per time unit as an item selection procedure for AMC. The latter procedure incorporates not only the amount of information provided by a given item but also the expected amount of time required to complete it. In a simulation study, the use of Fisher information per time unit item selection resulted in a lower false positive rate in the majority of conditions studied, and a higher true positive rate in all conditions studied, compared to item selection via Fisher information without accounting for the expected time taken. Future directions of research are suggested.

10aadaptive measurement of change10acomputerized adaptive testing10aFisher information10aitem selection10aresponse-time modeling1 aFinkelman, Matthew1 aWang, Chun uhttp://iacat.org/jcat/index.php/jcat/article/view/73/3501267nas a2200157 4500008003900000245009900039210006900138300001200207490000700219520076400226100001800990700001501008700001801023700002301041856004501064 2018 d00aA Continuous a-Stratification Index for Item Exposure Control in Computerized Adaptive Testing0 aContinuous aStratification Index for Item Exposure Control in Co a523-5370 v423 aThe method of a-stratification aims to reduce item overexposure in computerized adaptive testing, as items that are administered at very high rates may threaten the validity of test scores. In existing methods of a-stratification, the item bank is partitioned into a fixed number of nonoverlapping strata according to the items’a, or discrimination, parameters. This article introduces a continuous a-stratification index which incorporates exposure control into the item selection index itself and thus eliminates the need for fixed discrete strata. The new continuous a-stratification index is compared with existing stratification methods via simulation studies in terms of ability estimation bias, mean squared error, and control of item exposure rates.1 aHuebner, Alan1 aWang, Chun1 aDaly, Bridget1 aPinkelman, Colleen uhttps://doi.org/10.1177/014662161875828900515nas a2200133 4500008003900000245012900039210006900168300000900237490000600246100001800252700002700270700002400297856006000321 2018 d00aFactors Affecting the Classification Accuracy and Average Length of a Variable-Length Cognitive Diagnostic Computerized Test0 aFactors Affecting the Classification Accuracy and Average Length a1-140 v61 aHuebner, Alan1 aFinkelman, Matthew, D.1 aWeissman, Alexander uhttp://iacat.org/jcat/index.php/jcat/article/view/55/3001999nas a2200133 4500008003900000245011600039210006900155300001200224490000700236520154300243100001901786700001501805856004501820 2017 d00aApplication of Binary Searching for Item Exposure Control in Cognitive Diagnostic Computerized Adaptive Testing0 aApplication of Binary Searching for Item Exposure Control in Cog a561-5760 v413 aCognitive diagnosis has emerged as a new generation of testing theory for educational assessment after the item response theory (IRT). One distinct feature of cognitive diagnostic models (CDMs) is that they assume the latent trait to be discrete instead of continuous as in IRT. From this perspective, cognitive diagnosis bears a close resemblance to searching problems in computer science and, similarly, item selection problem in cognitive diagnostic computerized adaptive testing (CD-CAT) can be considered as a dynamic searching problem. Previously, item selection algorithms in CD-CAT were developed from information indices in information science and attempted to achieve a balance among several objectives by assigning different weights. As a result, they suffered from low efficiency from a tug-of-war competition among multiple goals in item selection and, at the same time, put an undue responsibility of assigning the weights for these goals by trial and error on users. Based on the searching problem perspective on CD-CAT, this article adapts the binary searching algorithm, one of the most well-known searching algorithms in searching problems, to item selection in CD-CAT. The two new methods, the stratified dynamic binary searching (SDBS) algorithm for fixed-length CD-CAT and the dynamic binary searching (DBS) algorithm for variable-length CD-CAT, can achieve multiple goals without any of the aforementioned issues. The simulation studies indicate their performances are comparable or superior to the previous methods.1 aZheng, Chanjin1 aWang, Chun uhttps://doi.org/10.1177/014662161770750903032nas a2200169 4500008004100000245004800041210004300089260005500132520252300187653001002710653001802720100001902738700001702757700001402774700001602788856005802804 2017 eng d00aThe Development of a Web-Based CAT in China0 aDevelopment of a WebBased CAT in China aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Cognitive ability assessment has been widely used as the recruitment tool in hiring potential employees. Traditional cognitive ability tests have been encountering threats from item-exposures and long time for answering. Especially in China, campus recruitment thinks highly of short answering time and anti-cheating. Beisen, as the biggest native online assessment software provider, developed a web-based CAT for cognitive ability which assessing verbal, quantitative, logical and spatial ability in order to decrease answering times, improve assessment accuracy and reduce threats from cheating and faking in online ability test. The web-based test provides convenient testing for examinees who can access easily to the test via internet just by login the test website at any time and any place through any Internet-enabled devices (e.g., laptops, IPADs, and smart phones).

We designed the CAT following strategies of establishing item bank, setting starting point, item selection, scoring and terminating. Additionally, we pay close attention to administrating the test via web. For the CAT procedures, we employed online calibration for establishing a stable and expanding item bank, and integrated maximum Fisher information, α-stratified strategy and randomization for item selection and coping with item exposures. Fixed-length and variable-length strategies were combined in terminating the test. For fulfilling the fluid web-based testing, we employed cloud computing techniques and designed each computing process subtly. Distributed computation was used to process scoring which executes EAP and item selecting at high speed. Caching all items to the servers in advance helps shortening the process of loading items to examinees’ terminal equipment. Horizontally scalable cloud servers function coping with great concurrency. The massive computation in item selecting was conversed to searching items from an information matrix table.

We examined the average accuracy, bank usage and computing performance in the condition of laboratory and real testing. According to a test for almost 28000 examinees, we found that bank usage is averagely 50%, and that 80% tests terminate at test information of 10 and averagely at 9.6. In context of great concurrency, the testing is unhindered and the process of scoring and item selection only takes averagely 0.23s for each examiner.

Session Video

10aChina10aWeb-Based CAT1 aLiang, Chongli1 aWang, Danjun1 aZhou, Dan1 aZhan, Peida uhttp://mail.iacat.org/development-web-based-cat-china03946nas a2200181 4500008004100000245009300041210006900134260005500203520329800258653001203556653002403568653002603592653002503618100001403643700002103657700001503678856007103693 2017 eng d00aDIF-CAT: Doubly Adaptive CAT Using Subgroup Information to Improve Measurement Precision0 aDIFCAT Doubly Adaptive CAT Using Subgroup Information to Improve aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Differential item functioning (DIF) is usually regarded as a test fairness issue in high-stakes tests. In low-stakes tests, it is more of an accuracy problem. However, in low-stakes tests, the same method, deleting items that demonstrate significant DIF, is still employed to treat DIF items. When political concerns are not important, such as in low-stakes tests and instruments that are not used to make decisions about people, deleting items might not be optimal. Computerized adaptive testing (CAT) is more and more frequently used in low-stakes tests. The DIF-CAT method evaluated in this research is designed to cope with DIF in a CAT environment. Using this method, item parameters are separately estimated for the focal group and the reference group in a DIF study, then CATs are administered based on different sets of item parameters for the focal and reference groups.

To evaluate the performance of the DIF-CAT procedure, it was compared in a simulation study to (1) deleting all the DIF items in a CAT bank and (2) ignoring DIF. A 300-item flat item bank and a 300-item peaked item bank were simulated using the three-parameter logistic IRT model with D = 1,7. 40% of the items in each bank showed DIF. The DIF size was b and/or a = 0.5 while original b ranged from -3 to 3 and a ranged from 0.3 to 2.1. Three types of DIF were considered: (1) uniform DIF caused by differences in b, non-uniform DIF caused by differences in a, and non-uniform DIF caused by differences in both a and b. 500 normally distributed simulees in each of reference and focal groups were used in item parameter re-calibration. In the Delete DIF method, only DIF-free items were calibrated. In the Ignore DIF method, all the items were calibrated using all simulees without differentiating the groups. In the DIF-CAT method, the DIF-free items were used as anchor items to estimate the item parameters for the focal and reference groups and the item parameters from recalibration were used. All simulees used the same item parameters in the Delete method and the Ignore method. CATs for simulees within the two groups used group-specific item parameters in the DIF-CAT method. In the CAT stage, 100 simulees were generated for each of the reference and focal groups, at each of six discrete q levels ranging from -2.5 to 2.5. CAT test length was fixed at 40 items. Bias, average absolute difference, RMSE, standard error of θ estimates, and person fit, were used to compare the performance of the DIF methods. DIF item usage was also recorded for the Ignore method and the DIF-CAT method.

Generally, the DIF-CAT method outperformed both the Delete method and the Ignore method in dealing with DIF items in CAT. The Delete method, which is the most frequently used method for handling DIF, performed the worst of the three methods in a CAT environment, as reflected in multiple indices of measurement precision. Even the Ignore method, which simply left DIF items in the item bank, provided θ estimates of higher precision than the Delete method. This poor performance of the Delete method was probably due to reduction in size of the item bank available for each CAT.

Session Video

10aDIF-CAT10aDoubly Adaptive CAT10aMeasurement Precision10asubgroup information1 aWang, Joy1 aWeiss, David, J.1 aWang, Chun uhttps://drive.google.com/open?id=1Gu4FR06qM5EZNp_Ns0Kt3HzBqWAv3LPy02365nas a2200277 4500008004100000245007100041210006900112260005500181520152900236653000801765653001501773653002801788100001501816700002101831700001501852700001401867700001601881700001501897700001601912700001601928700001601944700001801960700001901978700001901997856007102016 2017 eng d00aNew Challenges (With Solutions) and Innovative Applications of CAT0 aNew Challenges With Solutions and Innovative Applications of CAT aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Over the past several decades, computerized adaptive testing (CAT) has profoundly changed the administration of large-scale aptitude tests, state-wide achievement tests, professional licensure exams, and health outcome measures. While many challenges of CAT have been successfully addressed due to the continual efforts of researchers in the field, there are still many remaining, longstanding challenges that have yet to be resolved. This symposium will begin with three presentations, each of which provides a sound solution to one of the unresolved challenges. They are (1) item calibration when responses are “missing not at random” from CAT administration; (2) online calibration of new items when person traits have non-ignorable measurement error; (3) establishing consistency and asymptotic normality of latent trait estimation when allowing item response revision in CAT. In addition, this symposium also features innovative applications of CAT. In particular, there is emerging interest in using cognitive diagnostic CAT to monitor and detect learning progress (4th presentation). Last but not least, the 5th presentation illustrates the power of multidimensional polytomous CAT that permits rapid identification of hospitalized patients’ rehabilitative care needs in health outcomes measurement. We believe this symposium covers a wide range of interesting and important topics in CAT.

Session Video

10aCAT10achallenges10ainnovative applications1 aWang, Chun1 aWeiss, David, J.1 aZhang, Xue1 aTao, Jian1 aHe, Yinhong1 aChen, Ping1 aWang, Shiyu1 aZhang, Susu1 aLin, Haiyan1 aGao, Xiaohong1 aChang, Hua-Hua1 aShang, Zhuoran uhttps://drive.google.com/open?id=1Wvgxw7in_QCq_F7kzID6zCZuVXWcFDPa03598nas a2200169 4500008004100000245004300041210004100084260005500125520306600180653000803246653002303254653002303277100001703300700002003317700002003337856007103357 2017 eng d00aScripted On-the-fly Multistage Testing0 aScripted Onthefly Multistage Testing aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

On-the-fly multistage testing (OMST) was introduced recently as a promising alternative to preassembled MST. A decidedly appealing feature of both is the reviewability of items within the current stage. However, the fundamental difference is that, instead of routing to a preassembled module, OMST adaptively assembles a module at each stage according to an interim ability estimate. This produces more individualized forms with finer measurement precision, but imposing nonstatistical constraints and controlling item exposure become more cumbersome. One recommendation is to use the maximum priority index followed by a remediation step to satisfy content constraints, and the Sympson-Hetter method with a stratified item bank for exposure control.

However, these methods can be computationally expensive, thereby impeding practical implementation. Therefore, this study investigated the script method as a simpler solution to the challenge of strict content balancing and effective item exposure control in OMST. The script method was originally devised as an item selection algorithm for CAT and generally proceeds as follows: For a test with m items, there are m slots to be filled, and an item is selected according to pre-defined rules for each slot. For the first slot, randomly select an item from a designated content area (collection). For each subsequent slot, 1) Discard any enemies of items already administered in previous slots; 2) Draw a designated number of candidate items (selection length) from the designated collection according to the current ability estimate; 3) Randomly select one item from the set of candidates. There are two distinct features of the script method. First, a predetermined sequence of collections guarantees meeting content specifications. The specific ordering may be determined either randomly or deliberately by content experts. Second, steps 2 and 3 depict a method of exposure control, in which selection length balances item usage at the possible expense of ability estimation accuracy. The adaptation of the script method to OMST is straightforward. For the first module, randomly select each item from a designated collection. For each subsequent module, the process is the same as in scripted CAT (SCAT) except the same ability estimate is used for the selection of all items within the module. A series of simulations was conducted to evaluate the performance of scripted OMST (SOMST, with 3 or 4 evenly divided stages) relative to SCAT under various item exposure restrictions. In all conditions, reliability was maximized by programming an optimization algorithm that searches for the smallest possible selection length for each slot within the constraints. Preliminary results indicated that SOMST is certainly a capable design with performance comparable to that of SCAT. The encouraging findings and ease of implementation highly motivate the prospect of operational use for large-scale assessments.

Presentation Video

10aCAT10amultistage testing10aOn-the-fly testing1 aChoe, Edison1 aWilliams, Bruce1 aLee, Sung-Hyuck uhttps://drive.google.com/open?id=1wKuAstITLXo6BM4APf2mPsth1BymNl-y02153nas a2200157 4500008004100000245008800041210006900129260005400198520153900252653002901791653001101820100001901831700002001850700001801870856010701888 2017 eng d00aUsing Bayesian Decision Theory in Cognitive Diagnosis Computerized Adaptive Testing0 aUsing Bayesian Decision Theory in Cognitive Diagnosis Computeriz aNiigata JapanbNiigata Seiryo Universityc08/20173 a

Cognitive diagnosis computerized adaptive testing (CD-CAT) purports to provide each individual a profile about the strengths and weaknesses of attributes or skills with computerized adaptive testing. In the CD-CAT literature, researchers dedicated to evolving item selection algorithms to improve measurement efficiency, and most algorithms were developed based on information theory. By the discontinuous nature of the latent variables in CD-CAT, this study introduced an alternative for item selection, called the minimum expected cost (MEC) method, which was derived based on Bayesian decision theory. Using simulations, the MEC method was evaluated against the posterior weighted Kullback-Leibler (PWKL) information, the modified PWKL (MPWKL), and the mutual information (MI) methods by manipulating item bank quality, item selection algorithm, and termination rule. Results indicated that, regardless of item quality and termination criterion, the MEC, MPWKL, and MI methods performed very similarly and they all outperformed the PWKL method in classification accuracy and test efficiency, especially in short tests; the MEC method had more efficient item bank usage than the MPWKL and MI methods. Moreover, the MEC method could consider the costs of incorrect decisions and improve classification accuracy and test efficiency when a particular profile was of concern. All the results suggest the practicability of the MEC method in CD-CAT.

Session Video

10aBayesian Decision Theory10aCD-CAT1 aHsu, Chia-Ling1 aWang, Wen-Chung1 aChen, ShuYing uhttp://mail.iacat.org/using-bayesian-decision-theory-cognitive-diagnosis-computerized-adaptive-testing04520nas a2200181 4500008004100000245010800041210006900149260005500218520381200273653000804085653002404093653002604117100001604143700001204159700001604171700002004187856013104207 2017 eng d00aUsing Computerized Adaptive Testing to Detect Students’ Misconceptions: Exploration of Item Selection0 aUsing Computerized Adaptive Testing to Detect Students Misconcep aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Owning misconceptions impedes learning, thus detecting misconceptions through assessments is crucial to facilitate teaching. However, most computerized adaptive testing (CAT) applications to diagnose examinees’ attribute profiles focus on whether examinees mastering correct concepts or not. In educational scenario, teachers and students have to figure out the misconceptions underlying incorrect answers after obtaining the scores from assessments and then correct the corresponding misconceptions. The Scaling Individuals and Classifying Misconceptions (SICM) models proposed by Bradshaw and Templin (2014) fill this gap. SICMs can identify a student’s misconceptions directly from the distractors of multiple-choice questions and report whether s/he own the misconceptions or not. Simultaneously, SICM models are able to estimate a continuous ability within the item response theory (IRT) framework to fulfill the needs of policy-driven assessment systems relying on scaling examinees’ ability. However, the advantage of providing estimations for two types of latent variables also causes complexity of model estimation. More items are required to achieve the same accuracies for both classification and estimation compared to dichotomous DCMs and to IRT, respectively. Thus, we aim to develop a CAT using the SICM models (SICM-CAT) to estimate students’ misconceptions and continuous abilities simultaneously using fewer items than a linear test.

To achieve this goal, in this study, our research questions mainly focus on establishing several item selection rules that target on providing both accurate classification results and continuous ability estimations using SICM-CAT. The first research question is which information criterion to be used. The Kullback–Leibler (KL) divergence is the first choice, as it can naturally combine the continuous and discrete latent variables. Based on this criterion, we propose an item selection index that can nicely integrate the two types of information. Based on this index, the items selected in real time could discriminate the examinee’s current misconception profile and ability estimates from other possible estimates to the most extent. The second research question is about how to adaptively balance the estimations of the misconception profile and the continuous latent ability. Mimic the idea of the Hybrid Design proposed by Wang et al. (2016), we propose a design framework which makes the item selection transition from the group-level to the item-level. We aim to explore several design questions, such as how to select the transiting point and which latent variable estimation should be targeted first.

Preliminary results indicated that the SICM-CAT based on the proposed item selection index could classify examinees into different latent classes and measure their latent abilities compared with the random selection method more accurately and reliably under all the simulation conditions. We plan to compare different CAT designs based on our proposed item selection rules with the best linear test as the next step. We expect that the SICM-CAT is able to use shorter test length while retaining the same accuracies and reliabilities.

References

Bradshaw, L., & Templin, J. (2014). Combining item response theory and diagnostic classification models: A psychometric model for scaling ability and diagnosing misconceptions. Psychometrika, 79(3), 403-425.

Wang, S., Lin, H., Chang, H. H., & Douglas, J. (2016). Hybrid computerized adaptive testing: from group sequential design to fully sequential design. Journal of Educational Measurement, 53(1), 45-62.

Session Video

10aCAT10aincorrect answering10aStudent Misconception1 aShen, Yawei1 aBao, Yu1 aWang, Shiyu1 aBradshaw, Laine uhttp://mail.iacat.org/using-computerized-adaptive-testing-detect-students%E2%80%99-misconceptions-exploration-item-selection-001269nas a2200301 4500008003900000022001400039245021000053210006900263260000800332300001600340490000700356520033300363100001600696700001300712700001400725700001900739700001600758700001500774700001500789700001500804700002000819700001400839700001400853700001800867700001200885700002400897856004600921 2017 d a1573-264900aThe validation of a computer-adaptive test (CAT) for assessing health-related quality of life in children and adolescents in a clinical sample: study design, methods and first results of the Kids-CAT study0 avalidation of a computeradaptive test CAT for assessing healthre cMay a1105–11170 v263 aRecently, we developed a computer-adaptive test (CAT) for assessing health-related quality of life (HRQoL) in children and adolescents: the Kids-CAT. It measures five generic HRQoL dimensions. The aims of this article were (1) to present the study design and (2) to investigate its psychometric properties in a clinical setting.1 aBarthel, D.1 aOtto, C.1 aNolte, S.1 aMeyrose, A.-K.1 aFischer, F.1 aDevine, J.1 aWalter, O.1 aMierke, A.1 aFischer, K., I.1 aThyen, U.1 aKlein, M.1 aAnkermann, T.1 aRose, M1 aRavens-Sieberer, U. uhttps://doi.org/10.1007/s11136-016-1437-901608nas a2200169 4500008003900000022001400039245009800053210006900151300001200220490000700232520108900239100001601328700001601344700001901360700001801379856004101397 2016 d a1745-398400aHybrid Computerized Adaptive Testing: From Group Sequential Design to Fully Sequential Design0 aHybrid Computerized Adaptive Testing From Group Sequential Desig a45–620 v533 aComputerized adaptive testing (CAT) and multistage testing (MST) have become two of the most popular modes in large-scale computer-based sequential testing.  Though most designs of CAT and MST exhibit strength and weakness in recent large-scale implementations, there is no simple answer to the question of which design is better because different modes may fit different practical situations. This article proposes a hybrid adaptive framework to combine both CAT and MST, inspired by an analysis of the history of CAT and MST. The proposed procedure is a design which transitions from a group sequential design to a fully sequential design. This allows for the robustness of MST in early stages, but also shares the advantages of CAT in later stages with fine tuning of the ability estimator once its neighborhood has been identified. Simulation results showed that hybrid designs following our proposed principles provided comparable or even better estimation accuracy and efficiency than standard CAT and MST designs, especially for examinees at the two ends of the ability range.1 aWang, Shiyu1 aLin, Haiyan1 aChang, Hua-Hua1 aDouglas, Jeff uhttp://dx.doi.org/10.1111/jedm.1210001299nas a2200145 4500008003900000022001400039245009100053210006900144300001300213490000700226520083800233100002101071700002001092856004101112 2016 d a1745-398400aModeling Student Test-Taking Motivation in the Context of an Adaptive Achievement Test0 aModeling Student TestTaking Motivation in the Context of an Adap a86–1050 v533 aThis study examined the utility of response time-based analyses in understanding the behavior of unmotivated test takers. For the data from an adaptive achievement test, patterns of observed rapid-guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent unmotivated test taking behavior. Test taker behavior was found to be inconsistent with these models, with the exception of the effort-moderated model. Effort-moderated scoring was found to both yield scores that were more accurate than those found under traditional scoring, and exhibit improved person fit statistics. In addition, an effort-guided adaptive test was proposed and shown by a simulation study to alleviate item difficulty mistargeting caused by unmotivated test taking.1 aWise, Steven, L.1 aKingsbury, Gage uhttp://dx.doi.org/10.1111/jedm.1210201700nas a2200145 4500008003900000245009300039210006900132490000700201520118000208100001301388700001901401700001501420700001101435856010801446 2016 d00aUsing Response Time to Detect Item Preknowledge in Computer?Based Licensure Examinations0 aUsing Response Time to Detect Item Preknowledge in ComputerBased0 v353 aThis article addresses the issue of how to detect item preknowledge using item response time data in two computer-based large-scale licensure examinations. Item preknowledge is indicated by an unexpected short response time and a correct response. Two samples were used for detecting item preknowledge for each examination. The first sample was from the early stage of the operational test and was used for item calibration. The second sample was from the late stage of the operational test, which may feature item preknowledge. The purpose of this research was to explore whether there was evidence of item preknowledge and compromised items in the second sample using the parameters estimated from the first sample. The results showed that for one nonadaptive operational examination, two items (of 111) were potentially exposed, and two candidates (of 1,172) showed some indications of preknowledge on multiple items. For another licensure examination that featured computerized adaptive testing, there was no indication of item preknowledge or compromised items. Implications for detected aberrant examinees and compromised items are discussed in the article.1 aH., Qian1 aStaniewska, D.1 aReckase, M1 aWoo, A uhttp://mail.iacat.org/using-response-time-detect-item-preknowledge-computerbased-licensure-examinations01559nas a2200169 4500008003900000022001400039245007700053210006900130300001300199490000700212520105800219100002101277700001401298700001901312700001701331856004101348 2015 d a1745-398400aAssessing Individual-Level Impact of Interruptions During Online Testing0 aAssessing IndividualLevel Impact of Interruptions During Online  a80–1050 v523 aWith an increase in the number of online tests, the number of interruptions during testing due to unexpected technical issues seems to be on the rise. For example, interruptions occurred during several recent state tests. When interruptions occur, it is important to determine the extent of their impact on the examinees' scores. Researchers such as Hill and Sinharay et al. examined the impact of interruptions at an aggregate level. However, there is a lack of research on the assessment of impact of interruptions at an individual level. We attempt to fill that void. We suggest four methodological approaches, primarily based on statistical hypothesis testing, linear regression, and item response theory, which can provide evidence on the individual-level impact of interruptions. We perform a realistic simulation study to compare the Type I error rate and power of the suggested approaches. We then apply the approaches to data from the 2013 Indiana Statewide Testing for Educational Progress-Plus (ISTEP+) test that experienced interruptions.1 aSinharay, Sandip1 aWan, Ping1 aChoi, Seung, W1 aKim, Dong-In uhttp://dx.doi.org/10.1111/jedm.1206401735nas a2200133 4500008003900000245009100039210006900130300001200199490000700211520129100218100001801509700002101527856005301548 2015 d00aBest Design for Multidimensional Computerized Adaptive Testing With the Bifactor Model0 aBest Design for Multidimensional Computerized Adaptive Testing W a954-9780 v753 aMost computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm (MCAT) with a bifactor model using simulated data. Four item selection methods in MCAT were examined for three bifactor pattern designs using two multidimensional item response theory models. To compare MCAT item selection and estimation methods, a fixed test length was used. The Ds-optimality item selection improved θ estimates with respect to a general factor, and either D- or A-optimality improved estimates of the group factors in three bifactor pattern designs under two multidimensional item response theory models. The MCAT model without a guessing parameter functioned better than the MCAT model with a guessing parameter. The MAP (maximum a posteriori) estimation method provided more accurate θ estimates than the EAP (expected a posteriori) method under most conditions, and MAP showed lower observed standard errors than EAP under most conditions, except for a general factor condition using Ds-optimality item selection.1 aSeo, Dong, Gi1 aWeiss, David, J. uhttp://epm.sagepub.com/content/75/6/954.abstract01279nas a2200121 4500008003900000245009800039210006900137490000700206520079800213100001701011700001901028856011001047 2015 d00aConsidering the Use of General and Modified Assessment Items in Computerized Adaptive Testing0 aConsidering the Use of General and Modified Assessment Items in 0 v283 aThis article used several data sets from a large-scale state testing program to examine the feasibility of combining general and modified assessment items in computerized adaptive testing (CAT) for different groups of students. Results suggested that several of the assumptions made when employing this type of mixed-item CAT may not be met for students with disabilities that have typically taken alternate assessments based on modified achievement standards (AA-MAS). A simulation study indicated that the abilities of AA-MAS students can be underestimated or overestimated by the mixed-item CAT, depending on students’ location on the underlying ability scale. These findings held across grade levels and test lengths. The mixed-item CAT appeared to function well for non-AA-MAS students.1 aWyse, A., E.1 aAlbano, A., D. uhttp://mail.iacat.org/considering-use-general-and-modified-assessment-items-computerized-adaptive-testing01076nas a2200133 4500008003900000245006600039210006600105490000700171520062900178100001400807700001900821700001700840856008500857 2015 d00aEvaluating Content Alignment in Computerized Adaptive Testing0 aEvaluating Content Alignment in Computerized Adaptive Testing0 v343 aThe alignment between a test and the content domain it measures represents key evidence for the validation of test score inferences. Although procedures have been developed for evaluating the content alignment of linear tests, these procedures are not readily applicable to computerized adaptive tests (CATs), which require large item pools and do not use fixed test forms. This article describes the decisions made in the development of CATs that influence and might threaten content alignment. It outlines a process for evaluating alignment that is sensitive to these threats and gives an empirical example of the process.1 aWise, S L1 aKingsbury, G G1 aWebb, N., L. uhttp://mail.iacat.org/evaluating-content-alignment-computerized-adaptive-testing01274nas a2200121 4500008003900000245006200039210006000101490000700161520088200168100001201050700001201062856007801074 2015 d00aUsing Out-of-Level Items in Computerized Adaptive Testing0 aUsing OutofLevel Items in Computerized Adaptive Testing0 v153 aOut-of-level testing refers to the practice of assessing a student with a test that is intended for students at a higher or lower grade level. Although the appropriateness of out-of-level testing for accountability purposes has been questioned by educators and policymakers, incorporating out-of-level items in formative assessments for accurate feedback is recommended. This study made use of a commercial item bank with vertically scaled items across grades and simulated student responses in a computerized adaptive testing (CAT) environment. Results of the study suggested that administration of out-of-level items improved measurement accuracy and test efficiency for students who perform significantly above or below their grade-level peers. This study has direct implications with regards to the relevance, applicability, and benefits of using out-of-level items in CAT.1 aWei, H.1 aLin, J. uhttp://mail.iacat.org/using-out-level-items-computerized-adaptive-testing01714nas a2200145 4500008003900000022001400039245008400053210006900137300001400206490000700220520126100227100001901488700002001507856004101527 2015 d a1745-398400aVariable-Length Computerized Adaptive Testing Using the Higher Order DINA Model0 aVariableLength Computerized Adaptive Testing Using the Higher Or a125–1430 v523 aCognitive diagnosis models provide profile information about a set of latent binary attributes, whereas item response models yield a summary report on a latent continuous trait. To utilize the advantages of both models, higher order cognitive diagnosis models were developed in which information about both latent binary attributes and latent continuous traits is available. To facilitate the utility of cognitive diagnosis models, corresponding computerized adaptive testing (CAT) algorithms were developed. Most of them adopt the fixed-length rule to terminate CAT and are limited to ordinary cognitive diagnosis models. In this study, the higher order deterministic-input, noisy-and-gate (DINA) model was used as an example, and three criteria based on the minimum-precision termination rule were implemented: one for the latent class, one for the latent trait, and the other for both. The simulation results demonstrated that all of the termination criteria were successful when items were selected according to the Kullback-Leibler information and the posterior-weighted Kullback-Leibler information, and the minimum-precision rule outperformed the fixed-length rule with a similar test length in recovering the latent attributes and the latent trait.1 aHsu, Chia-Ling1 aWang, Wen-Chung uhttp://dx.doi.org/10.1111/jedm.1206900532nas a2200145 4500008004500000245013100045210006900176300001000245490000600255100001900261700001100280700001600291700001500307856006400322 2014 Engldsh 00aCognitive Diagnostic Models and Computerized Adaptive Testing: Two New Item-Selection Methods That Incorporate Response Times0 aCognitive Diagnostic Models and Computerized Adaptive Testing Tw a59-760 v21 aFinkelman, M D1 aKim, W1 aWeissman, A1 aCook, R.J. uhttp://www.iacat.org/jcat/index.php/jcat/article/view/43/2101617nas a2200193 4500008003900000022001400039245007400053210006900127300001400196490000700210520105700217100002101274700001401295700001901309700001701328700001801345700001901363856004101382 2014 d a1745-398400aDetermining the Overall Impact of Interruptions During Online Testing0 aDetermining the Overall Impact of Interruptions During Online Te a419–4400 v513 a

With an increase in the number of online tests, interruptions during testing due to unexpected technical issues seem unavoidable. For example, interruptions occurred during several recent state tests. When interruptions occur, it is important to determine the extent of their impact on the examinees’ scores. There is a lack of research on this topic due to the novelty of the problem. This article is an attempt to fill that void. Several methods, primarily based on propensity score matching, linear regression, and item response theory, were suggested to determine the overall impact of the interruptions on the examinees’ scores. A realistic simulation study shows that the suggested methods have satisfactory Type I error rate and power. Then the methods were applied to data from the Indiana Statewide Testing for Educational Progress-Plus (ISTEP+) test that experienced interruptions in 2013. The results indicate that the interruptions did not have a significant overall impact on the student scores for the ISTEP+ test.

1 aSinharay, Sandip1 aWan, Ping1 aWhitaker, Mike1 aKim, Dong-In1 aZhang, Litong1 aChoi, Seung, W uhttp://dx.doi.org/10.1111/jedm.1205201835nas a2200157 4500008003900000022001400039245010200053210006900155300001400224490000700238520133800245100001501583700001901598700001901617856004101636 2014 d a1745-398400aAn Enhanced Approach to Combine Item Response Theory With Cognitive Diagnosis in Adaptive Testing0 aEnhanced Approach to Combine Item Response Theory With Cognitive a358–3800 v513 a

Computerized adaptive testing offers the possibility of gaining information on both the overall ability and cognitive profile in a single assessment administration. Some algorithms aiming for these dual purposes have been proposed, including the shadow test approach, the dual information method (DIM), and the constraint weighted method. The current study proposed two new methods, aggregate ranked information index (ARI) and aggregate standardized information index (ASI), which appropriately addressed the noncompatibility issue inherent in the original DIM method. More flexible weighting schemes that put different emphasis on information about general ability (i.e., θ in item response theory) and information about cognitive profile (i.e., α in cognitive diagnostic modeling) were also explored. Two simulation studies were carried out to investigate the effectiveness of the new methods and weighting schemes. Results showed that the new methods with the flexible weighting schemes could produce more accurate estimation of both overall ability and cognitive profile than the original DIM. Among them, the ASI with both empirical and theoretical weights is recommended, and attribute-level weighting scheme is preferred if some attributes are considered more important from a substantive perspective.

1 aWang, Chun1 aZheng, Chanjin1 aChang, Hua-Hua uhttp://dx.doi.org/10.1111/jedm.1205701984nas a2200121 4500008003900000245008900039210006900128300001200197490000700209520157400216100001501790856005701805 2014 d00aImproving Measurement Precision of Hierarchical Latent Traits Using Adaptive Testing0 aImproving Measurement Precision of Hierarchical Latent Traits Us a452-4770 v393 a

Many latent traits in social sciences display a hierarchical structure, such as intelligence, cognitive ability, or personality. Usually a second-order factor is linearly related to a group of first-order factors (also called domain abilities in cognitive ability measures), and the first-order factors directly govern the actual item responses. Because only a subtest of items is used to measure each domain, the lack of sufficient reliability becomes the primary impediment for generating and reporting domain abilities. In recent years, several item response theory (IRT) models have been proposed to account for hierarchical factor structures, and these models are also shown to alleviate the low reliability issue by using in-test collateral information to improve measurement precision. This article advocates using adaptive item selection together with a higher order IRT model to further increase the reliability of hierarchical latent trait estimation. Two item selection algorithms are proposed—the constrained D-optimal method and the sequencing domain method. Both are shown to yield improved measurement precision as compared to the unidimensional item selection (by treating each dimension separately). The improvement is more prominent when the test length is short and when the correlation between dimensions is high (e.g., higher than .64). Moreover, two reliability indices for hierarchical latent traits are discussed and their use for quantifying the reliability of hierarchical traits measured by adaptive testing is demonstrated.

1 aWang, Chun uhttp://jeb.sagepub.com/cgi/content/abstract/39/6/45200446nas a2200109 4500008004500000245008700045210006900132300000900201490000600210100002000216856010000236 2014 Engldsh 00aThe Utility of Adaptive Testing in Addressing the Problem of Unmotivated Examinees0 aUtility of Adaptive Testing in Addressing the Problem of Unmotiv a1-170 v21 aWise, Steven, L uhttp://mail.iacat.org/content/utility-adaptive-testing-addressing-problem-unmotivated-examinees02198nas a2200145 4500008003900000245007900039210006900118300001100187490000700198520173800205100001501943700001901958700002301977856005202000 2013 d00aDeriving Stopping Rules for Multidimensional Computerized Adaptive Testing0 aDeriving Stopping Rules for Multidimensional Computerized Adapti a99-1220 v373 a

Multidimensional computerized adaptive testing (MCAT) is able to provide a vector of ability estimates for each examinee, which could be used to provide a more informative profile of an examinee’s performance. The current literature on MCAT focuses on the fixed-length tests, which can generate less accurate results for those examinees whose abilities are quite different from the average difficulty level of the item bank when there are only a limited number of items in the item bank. Therefore, instead of stopping the test with a predetermined fixed test length, the authors use a more informative stopping criterion that is directly related to measurement accuracy. Specifically, this research derives four stopping rules that either quantify the measurement precision of the ability vector (i.e., minimum determinant rule [D-rule], minimum eigenvalue rule [E-rule], and maximum trace rule [T-rule]) or quantify the amount of available information carried by each item (i.e., maximum Kullback–Leibler divergence rule [K-rule]). The simulation results showed that all four stopping rules successfully terminated the test when the mean squared error of ability estimation is within a desired range, regardless of examinees’ true abilities. It was found that when using the D-, E-, or T-rule, examinees with extreme abilities tended to have tests that were twice as long as the tests received by examinees with moderate abilities. However, the test length difference with K-rule is not very dramatic, indicating that K-rule may not be very sensitive to measurement precision. In all cases, the cutoff value for each stopping rule needs to be adjusted on a case-by-case basis to find an optimal solution.

1 aWang, Chun1 aChang, Hua-Hua1 aBoughton, Keith, A uhttp://apm.sagepub.com/content/37/2/99.abstract01865nas a2200121 4500008003900000245012200039210006900161300001400230490000700244520142300251100001501674856005401689 2013 d00aMutual Information Item Selection Method in Cognitive Diagnostic Computerized Adaptive Testing With Short Test Length0 aMutual Information Item Selection Method in Cognitive Diagnostic a1017-10350 v733 a

Cognitive diagnostic computerized adaptive testing (CD-CAT) purports to combine the strengths of both CAT and cognitive diagnosis. Cognitive diagnosis models aim at classifying examinees into the correct mastery profile group so as to pinpoint the strengths and weakness of each examinee whereas CAT algorithms choose items to determine those strengths and weakness as efficiently as possible. Most of the existing CD-CAT item selection algorithms are evaluated when test length is relatively long whereas several applications of CD-CAT, such as in interim assessment, require an item selection algorithm that is able to accurately recover examinees’ mastery profile with short test length. In this article, we introduce the mutual information item selection method in the context of CD-CAT and then provide a computationally easier formula to make the method more amenable in real time. Mutual information is then evaluated against common item selection methods, such as Kullback–Leibler information, posterior weighted Kullback–Leibler information, and Shannon entropy. Based on our simulations, mutual information consistently results in nearly the highest attribute and pattern recovery rate in more than half of the conditions. We conclude by discussing how the number of attributes, Q-matrix structure, correlations among the attributes, and item quality affect estimation accuracy.

1 aWang, Chun uhttp://epm.sagepub.com/content/73/6/1017.abstract01599nas a2200145 4500008003900000245010600039210006900145300001200214490000700226520111100233100002001344700001801364700001801382856005301400 2013 d00aThe Random-Threshold Generalized Unfolding Model and Its Application of Computerized Adaptive Testing0 aRandomThreshold Generalized Unfolding Model and Its Application  a179-2000 v373 a

The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs Sampler) freeware, which adopts a Bayesian approach for estimation. A series of simulations was conducted to evaluate the parameter recovery of the new model and the consequences of ignoring the randomness in thresholds. The results showed that the parameters of RTGUM were recovered fairly well and that ignoring the randomness in thresholds led to biased estimates. Computerized adaptive testing was also implemented on RTGUM, where the Fisher information criterion was used for item selection and the maximum a posteriori method was used for ability estimation. The simulation study showed that the longer the test length, the smaller the randomness in thresholds, and the more categories in an item, the more precise the ability estimates would be.

1 aWang, Wen-Chung1 aLiu, Chen-Wei1 aWu, Shiu-Lien uhttp://apm.sagepub.com/content/37/3/179.abstract01630nas a2200157 4500008003900000245010100039210006900140300001200209490000700221520111200228100001501340700001601355700001901371700002501390856005701415 2013 d00aA Semiparametric Model for Jointly Analyzing Response Times and Accuracy in Computerized Testing0 aSemiparametric Model for Jointly Analyzing Response Times and Ac a381-4170 v383 a

The item response times (RTs) collected from computerized testing represent an underutilized type of information about items and examinees. In addition to knowing the examinees’ responses to each item, we can investigate the amount of time examinees spend on each item. Current models for RTs mainly focus on parametric models, which have the advantage of conciseness, but may suffer from reduced flexibility to fit real data. We propose a semiparametric approach, specifically, the Cox proportional hazards model with a latent speed covariate to model the RTs, embedded within the hierarchical framework proposed by van der Linden to model the RTs and response accuracy simultaneously. This semiparametric approach combines the flexibility of nonparametric modeling and the brevity and interpretability of the parametric modeling. A Markov chain Monte Carlo method for parameter estimation is given and may be used with sparse data obtained by computerized adaptive testing. Both simulation studies and real data analysis are carried out to demonstrate the applicability of the new model.

1 aWang, Chun1 aFan, Zhewen1 aChang, Hua-Hua1 aDouglas, Jeffrey, A. uhttp://jeb.sagepub.com/cgi/content/abstract/38/4/38101716nas a2200145 4500008003900000245008600039210006900125300001200194490000700206520124600213100001901459700002001478700001901498856005301517 2013 d00aVariable-Length Computerized Adaptive Testing Based on Cognitive Diagnosis Models0 aVariableLength Computerized Adaptive Testing Based on Cognitive  a563-5820 v373 a

Interest in developing computerized adaptive testing (CAT) under cognitive diagnosis models (CDMs) has increased recently. CAT algorithms that use a fixed-length termination rule frequently lead to different degrees of measurement precision for different examinees. Fixed precision, in which the examinees receive the same degree of measurement precision, is a major advantage of CAT over nonadaptive testing. In addition to the precision issue, test security is another important issue in practical CAT programs. In this study, the authors implemented two termination criteria for the fixed-precision rule and evaluated their performance under two popular CDMs using simulations. The results showed that using the two criteria with the posterior-weighted Kullback–Leibler information procedure for selecting items could achieve the prespecified measurement precision. A control procedure was developed to control item exposure and test overlap simultaneously among examinees. The simulation results indicated that in contrast to no method of controlling exposure, the control procedure developed in this study could maintain item exposure and test overlap at the prespecified level at the expense of only a few more items.

1 aHsu, Chia-Ling1 aWang, Wen-Chung1 aChen, Shu-Ying uhttp://apm.sagepub.com/content/37/7/563.abstract01848nas a2200169 4500008004100000245012200041210006900163300001200232490000700244520124800251100001201499700001101511700001401522700001101536700001401547856011701561 2012 eng d00aComparison Between Dichotomous and Polytomous Scoring of Innovative Items in a Large-Scale Computerized Adaptive Test0 aComparison Between Dichotomous and Polytomous Scoring of Innovat a493-5090 v723 a

This study explored the impact of partial credit scoring of one type of innovative items (multiple-response items) in a computerized adaptive version of a large-scale licensure pretest and operational test settings. The impacts of partial credit scoring on the estimation of the ability parameters and classification decisions in operational test settings were explored in one real data analysis and two simulation studies when two different polytomous scoring algorithms, automated polytomous scoring and rater-generated polytomous scoring, were applied. For the real data analyses, the ability estimates from dichotomous and polytomous scoring were highly correlated; the classification consistency between different scoring algorithms was nearly perfect. Information distribution changed slightly in the operational item bank. In the two simulation studies comparing each polytomous scoring with dichotomous scoring, the ability estimates resulting from polytomous scoring had slightly higher measurement precision than those resulting from dichotomous scoring. The practical impact related to classification decision was minor because of the extremely small number of items that could be scored polytomously in this current study.

1 aJiao, H1 aLiu, J1 aHaynie, K1 aWoo, A1 aGorham, J uhttp://mail.iacat.org/content/comparison-between-dichotomous-and-polytomous-scoring-innovative-items-large-scale01240nas a2200145 4500008003900000245009000039210006900129300001200198490000700210520076800217100001900985700001701004700002001021856005301041 2012 d00aComputerized Adaptive Testing Using a Class of High-Order Item Response Theory Models0 aComputerized Adaptive Testing Using a Class of HighOrder Item Re a689-7060 v363 a

In the human sciences, a common assumption is that latent traits have a hierarchical structure. Higher order item response theory models have been developed to account for this hierarchy. In this study, computerized adaptive testing (CAT) algorithms based on these kinds of models were implemented, and their performance under a variety of situations was examined using simulations. The results showed that the CAT algorithms were very effective. The progressive method for item selection, the Sympson and Hetter method with online and freeze procedure for item exposure control, and the multinomial model for content balancing can simultaneously maintain good measurement precision, item exposure control, content balance, test security, and pool usage.

1 aHuang, Hung-Yu1 aChen, Po-Hsi1 aWang, Wen-Chung uhttp://apm.sagepub.com/content/36/8/689.abstract00541nas a2200181 4500008004500000245006300045210006300108300001400171490000700185100002300192700002000215700002200235700001700257700001600274700001800290700002100308856003000329 2012 Engldsh 00aDevelopment of a computerized adaptive test for depression0 aDevelopment of a computerized adaptive test for depression a1105-11120 v691 aGibbons, Robert, D1 aWeiss, David, J1 aPilkonis, Paul, A1 aFrank, Ellen1 aMoore, Tara1 aKim, Jong Bae1 aKupfer, David, J uWWW.ARCHGENPSYCHIATRY.COM00557nas a2200133 4500008004500000022001400045245012600059210006900185300000900254490000600263100001500269700001400284856012500298 2012 Engldsh  a2165-659200aTermination Criteria in Computerized Adaptive Tests: Do Variable-Length CATs Provide Efficient and Effective Measurement?0 aTermination Criteria in Computerized Adaptive Tests Do VariableL a1-180 v11 aBabcock, B1 aWeiss, DJ uhttp://mail.iacat.org/content/termination-criteria-computerized-adaptive-tests-do-variable-length-cats-provide-efficient02031nas a2200133 4500008003900000245007700039210006900116250001000185300000900195490001100204520156600215100001401781856010201795 2011 d00aBetter Data From Better Measurements Using Computerized Adaptive Testing0 aBetter Data From Better Measurements Using Computerized Adaptive aNo. 1 a1-270 vVol. 23 aThe process of constructing a fixed-length conventional test frequently focuses on maximizing internal consistency reliability by selecting test items that are of average difficulty and high discrimination (a ―peaked‖ test). The effect of constructing such a test, when viewed from the perspective of item response theory, is test scores that are precise for examinees whose trait levels are near the point at which the test is peaked; as examinee trait levels deviate from the mean, the precision of their scores decreases substantially. Results of a small simulation study demonstrate that when peaked tests are ―off target‖ for an examinee, their scores are biased and have spuriously high standard deviations, reflecting substantial amounts of error. These errors can reduce the correlations of these kinds of scores with other variables and adversely affect the results of standard statistical tests. By contrast, scores from adaptive tests are essentially unbiased and have standard deviations that are much closer to true values. Basic concepts of adaptive testing are introduced and fully adaptive computerized tests (CATs) based on IRT are described. Several examples of response records from CATs are discussed to illustrate how CATs function. Some operational issues, including item exposure, content balancing, and enemy items are also briefly discussed. It is concluded that because CAT constructs a unique test for examinee, scores from CATs will be more precise and should provide better data for social science research and applications.1 aWeiss, DJ uhttp://mail.iacat.org/content/better-data-better-measurements-using-computerized-adaptive-testing01961nas a2200193 4500008004100000020001400041245009500055210006900150300001200219490000700231520131000238100001501548700001801563700001701581700001401598700001301612700001901625856012301644 2011 eng d a0022-389100aComputerized adaptive assessment of personality disorder: Introducing the CAT–PD project0 aComputerized adaptive assessment of personality disorder Introdu a380-3890 v933 aAssessment of personality disorders (PD) has been hindered by reliance on the problematic categorical model embodied in the most recent Diagnostic and Statistical Model of Mental Disorders (DSM), lack of consensus among alternative dimensional models, and inefficient measurement methods. This article describes the rationale for and early results from a multiyear study funded by the National Institute of Mental Health that was designed to develop an integrative and comprehensive model and efficient measure of PD trait dimensions. To accomplish these goals, we are in the midst of a 5-phase project to develop and validate the model and measure. The results of Phase 1 of the project—which was focused on developing the PD traits to be assessed and the initial item pool—resulted in a candidate list of 59 PD traits and an initial item pool of 2,589 items. Data collection and structural analyses in community and patient samples will inform the ultimate structure of the measure, and computerized adaptive testing will permit efficient measurement of the resultant traits. The resultant Computerized Adaptive Test of Personality Disorder (CAT–PD) will be well positioned as a measure of the proposed DSM–5 PD traits. Implications for both applied and basic personality research are discussed.1 aSimms, L J1 aGoldberg, L R1 aRoberts, J E1 aWatson, D1 aWelte, J1 aRotterman, J H uhttp://mail.iacat.org/content/computerized-adaptive-assessment-personality-disorder-introducing-cat%E2%80%93pd-project01379nas a2200133 4500008003900000245008500039210006900124300001200193490000700205520094200212100002001154700001801174856005301192 2011 d00aComputerized Classification Testing Under the Generalized Graded Unfolding Model0 aComputerized Classification Testing Under the Generalized Graded a114-1280 v713 a

The generalized graded unfolding model (GGUM) has been recently developed to describe item responses to Likert items (agree—disagree) in attitude measurement. In this study, the authors (a) developed two item selection methods in computerized classification testing under the GGUM, the current estimate/ability confidence interval method and the cut score/sequential probability ratio test method and (b) evaluated their accuracy and efficiency in classification through simulations. The results indicated that both methods were very accurate and efficient. The more points each item had and the fewer the classification categories, the more accurate and efficient the classification would be. However, the latter method may yield a very low accuracy in dichotomous items with a short maximum test length. Thus, if it is to be used to classify examinees with dichotomous items, the maximum text length should be increased.

1 aWang, Wen-Chung1 aLiu, Chen-Wei uhttp://epm.sagepub.com/content/71/1/114.abstract01976nas a2200133 4500008003900000245011600039210006900155300001200224490000700236520150500243100002001748700002101768856005301789 2011 d00aComputerized Classification Testing Under the One-Parameter Logistic Response Model With Ability-Based Guessing0 aComputerized Classification Testing Under the OneParameter Logis a925-9410 v713 a

The one-parameter logistic model with ability-based guessing (1PL-AG) has been recently developed to account for effect of ability on guessing behavior in multiple-choice items. In this study, the authors developed algorithms for computerized classification testing under the 1PL-AG and conducted a series of simulations to evaluate their performances. Four item selection methods (the Fisher information, the Fisher information with a posterior distribution, the progressive method, and the adjusted progressive method) and two termination criteria (the ability confidence interval [ACI] method and the sequential probability ratio test [SPRT]) were developed. In addition, the Sympson–Hetter online method with freeze (SHOF) was implemented for item exposure control. Major results include the following: (a) when no item exposure control was made, all the four item selection methods yielded very similar correct classification rates, but the Fisher information method had the worst item bank usage and the highest item exposure rate; (b) SHOF can successfully maintain the item exposure rate at a prespecified level, without compromising substantial accuracy and efficiency in classification; (c) once SHOF was implemented, all the four methods performed almost identically; (d) ACI appeared to be slightly more efficient than SPRT; and (e) in general, a higher weight of ability in guessing led to a slightly higher accuracy and efficiency, and a lower forced classification rate.

1 aWang, Wen-Chung1 aHuang, Sheng-Yun uhttp://epm.sagepub.com/content/71/6/925.abstract01600nas a2200121 4500008004500000245011000045210006900155490000700224520114200231100001901373700001401392856007201406 2011 Engldsh 00aCreating a K-12 Adaptive Test: Examining the Stability of Item Parameter Estimates and Measurement Scales0 aCreating a K12 Adaptive Test Examining the Stability of Item Par0 v123 a

Development of adaptive tests used in K-12 settings requires the creation of stable measurement scales to measure the growth of individual students from one grade to the next, and to measure change in groups from one year to the next. Accountability systems
like No Child Left Behind require stable measurement scales so that accountability has meaning across time. This study examined the stability of the measurement scales used with the Measures of Academic Progress. Difficulty estimates for test questions from the reading and mathematics scales were examined over a period ranging from 7 to 22 years. Results showed high correlations between item difficulty estimates from the time at which they where originally calibrated and the current calibration. The average drift in item difficulty estimates was less than .01 standard deviations. The average impact of change in item difficulty estimates was less than the smallest reported difference on the score scale for two actual tests. The findings of the study indicate that an IRT scale can be stable enough to allow consistent measurement of student achievement.

1 aKingsbury, G G1 aWise, S L uhttp://www.testpublishers.org/journal-of-applied-testing-technology00938nas a2200133 4500008004100000245006700041210006500108260004700173490000700220520046100227100001800688700001400706856008400720 2011 eng d00aA framework for the development of computerized adaptive tests0 aframework for the development of computerized adaptive tests bPractical Assessment Research & Evaluation0 v163 aA substantial amount of research has been conducted over the past 40 years on technical aspects of computerized adaptive testing (CAT), such as item selection algorithms, item exposure controls, and termination criteria. However, there is little literature providing practical guidance on the development of a CAT. This paper seeks to collate some of the available research methodologies into a general framework for the development of any CAT assessment. 1 aThompson, N A1 aWeiss, DJ uhttp://mail.iacat.org/content/framework-development-computerized-adaptive-tests02532nas a2200205 4500008004100000245011900041210006900160260001200229520179400241653000802035653000802043653003402051653003002085653000802115653003102123653001602154653001302170100002002183856012302203 2011 eng d00aFrom Reliability to Validity: Expanding Adaptive Testing Practice to Find the Most Valid Score for Each Test Taker0 aFrom Reliability to Validity Expanding Adaptive Testing Practice c10/20113 a

CAT is an exception to the traditional conception of validity. It is one of the few examples of individualized testing. Item difficulty is tailored to each examinee. The intent, however, is increased efficiency. Focus on reliability (reduced standard error); Equivalence with paper & pencil tests is valued; Validity is enhanced through improved reliability.

How Else Might We Individualize Testing Using CAT?

An ISV-Based View of Validity

Test Event -- An examinee encounters a series of items in a particular context.

CAT Goal: individualize testing to address CIV threats to score validity (i.e., maximize ISV).

Some Research Issues:

10aCAT10aCIV10aconstruct-irrelevant variance10aIndividual Score Validity10aISV10alow test taking motivation10aReliability10avalidity1 aWise, Steven, L uhttp://mail.iacat.org/content/reliability-validity-expanding-adaptive-testing-practice-find-most-valid-score-each-test00483nas a2200145 4500008004100000245006100041210005900102653000800161653001600169653001300185100001900198700001600217700002200233856008200255 2011 eng d00aA Heuristic Of CAT Item Selection Procedure For Testlets0 aHeuristic Of CAT Item Selection Procedure For Testlets10aCAT10ashadow test10atestlets1 aChien, Yuehmei1 aShin, David1 aWay, Walter Denny uhttp://mail.iacat.org/content/heuristic-cat-item-selection-procedure-testlets00775nas a2200145 4500008004100000245005700041210005700098260001200155520031700167653001500484100001700499700001300516700001900529856008100548 2011 eng d00aImpact of Item Drift on Candidate Ability Estimation0 aImpact of Item Drift on Candidate Ability Estimation c10/20113 a

For large operational pools, candidate ability estimates appear robust to item drift, especially under conditions that may represent ‘normal’ amounts of drift. Even with ‘extreme’ conditions of drift (e.g., 20% of items drifting 1.00 logits), decision consistency was still high.

10aitem drift1 aHagge, Sarah1 aWoo, Ada1 aDickison, Phil uhttp://mail.iacat.org/content/impact-item-drift-candidate-ability-estimation00448nas a2200121 4500008004500000245006900045210006900114300001100183490000600194100001400200700001800214856009400232 2011 Engldsh 00aMeasuring Individual Growth With Conventional and Adaptive Tests0 aMeasuring Individual Growth With Conventional and Adaptive Tests a80-1010 v21 aWeiss, DJ1 aVon Minden, S uhttp://mail.iacat.org/content/measuring-individual-growth-conventional-and-adaptive-tests01546nas a2200109 4500008004500000245005800045210005400103490000700157520117100164100001501335856008601350 2011 Engldsh 00aNational Tests in Denmark – CAT as a Pedagogic Tool0 aNational Tests in Denmark CAT as a Pedagogic Tool0 v123 a

Testing and test results can be used in different ways. They can be used for regulation and control, but they can also be a pedagogic tool for assessment of student proficiency in order to target teaching, improve learning and facilitate local pedagogical leadership. To serve these purposes the test has to be used for low stakes purposes, and to ensure this, the Danish National test results are made strictly confidential by law. The only test results that are made public are the overall national results. Because of the test design, test results are directly comparable, offering potential for monitoring added value and developing new ways of using test results in a pedagogical context. This article gives the background and status for the development of the Danish national tests, describes what is special about these tests (e.g., Information Technology [IT]-based, 3 tests in 1, adaptive), how the national test are carried out, and what
is tested. Furthermore, it describes strategies for disseminating the results to the pupil, parents, teacher, headmaster and municipality; and how the results can be used by the teacher and headmaster.

1 aWandall, J uhttp://mail.iacat.org/content/national-tests-denmark-%E2%80%93-cat-pedagogic-tool01369nas a2200157 4500008003900000022001400039245010400053210006900157300001400226490000700240520085700247100001501104700001901119700001801138856005501156 2011 d a1745-398400aRestrictive Stochastic Item Selection Methods in Cognitive Diagnostic Computerized Adaptive Testing0 aRestrictive Stochastic Item Selection Methods in Cognitive Diagn a255–2730 v483 a

This paper proposes two new item selection methods for cognitive diagnostic computerized adaptive testing: the restrictive progressive method and the restrictive threshold method. They are built upon the posterior weighted Kullback-Leibler (KL) information index but include additional stochastic components either in the item selection index or in the item selection procedure. Simulation studies show that both methods are successful at simultaneously suppressing overexposed items and increasing the usage of underexposed items. Compared to item selection based upon (1) pure KL information and (2) the Sympson-Hetter method, the two new methods strike a better balance between item exposure control and measurement accuracy. The two new methods are also compared with Barrada et al.'s (2008) progressive method and proportional method.

1 aWang, Chun1 aChang, Hua-Hua1 aHuebner, Alan uhttp://dx.doi.org/10.1111/j.1745-3984.2011.00145.x00361nas a2200097 4500008004100000245005600041210005600097300001200153100001600165856008200181 2010 eng d00aAdaptive Tests for Measuring Anxiety and Depression0 aAdaptive Tests for Measuring Anxiety and Depression a123-1361 aWalter, O B uhttp://mail.iacat.org/content/adaptive-tests-measuring-anxiety-and-depression01512nas a2200217 4500008004100000245008100041210006900122300001200191490000700203520078900210653001100999653003401010653002201044653003501066653002101101653002101122100001901143700001401162700001601176856010201192 2010 eng d00aItem Selection and Hypothesis Testing for the Adaptive Measurement of Change0 aItem Selection and Hypothesis Testing for the Adaptive Measureme a238-2540 v343 a

Assessing individual change is an important topic in both psychological and educational measurement. An adaptive measurement of change (AMC) method had previously been shown to exhibit greater efficiency in detecting change than conventional nonadaptive methods. However, little work had been done to compare different procedures within the AMC framework. This study introduced a new item selection criterion and two new test statistics for detecting change with AMC that were specifically designed for the paradigm of hypothesis testing. In two simulation sets, the new methods for detecting significant change improved on existing procedures by demonstrating better adherence to Type I error rates and substantially better power for detecting relatively small change. 

10achange10acomputerized adaptive testing10aindividual change10aKullback–Leibler information10alikelihood ratio10ameasuring change1 aFinkelman, M D1 aWeiss, DJ1 aKim-Kang, G uhttp://mail.iacat.org/content/item-selection-and-hypothesis-testing-adaptive-measurement-change-000482nas a2200109 4500008004100000245008100041210006900122260004900191100001400240700001500254856010300269 2010 eng d00aManual for CATSim: Comprehensive simulation of computerized adaptive testing0 aManual for CATSim Comprehensive simulation of computerized adapt aSt. Paul, MNbAssessment Systems Corporation1 aWeiss, DJ1 aGuyer, R D uhttp://mail.iacat.org/content/manual-catsim-comprehensive-simulation-computerized-adaptive-testing00561nas a2200145 4500008003900000245015500039210006900194300001200263490000700275100001700282700001400299700001800313700001600331856006800347 2010 d00aA Monte Carlo Simulation Investigating the Validity and Reliability of Ability Estimation in Item Response Theory with Speeded Computer Adaptive Tests0 aMonte Carlo Simulation Investigating the Validity and Reliabilit a230-2610 v101 aSchmitt, T A1 aSass, D A1 aSullivan, J R1 aWalker, C M uhttp://www.tandfonline.com/doi/abs/10.1080/15305058.2010.48809800460nas a2200097 4500008004100000245010100041210006900142100001500211700001400226856012200240 2009 eng d00aComputerized adaptive testing using the two parameter logistic model with ability-based guessing0 aComputerized adaptive testing using the two parameter logistic m1 aShih, H -J1 aWang, W-C uhttp://mail.iacat.org/content/computerized-adaptive-testing-using-two-parameter-logistic-model-ability-based-guessing00567nas a2200109 4500008004100000245010000041210006900141260009700210100001500307700001600322856011900338 2009 eng d00aComputerized classification testing in more than two categories by using stochastic curtailment0 aComputerized classification testing in more than two categories  aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aWouda, J T1 aEggen, Theo uhttp://mail.iacat.org/content/computerized-classification-testing-more-two-categories-using-stochastic-curtailment00514nas a2200109 4500008004100000245006900041210006900110260009700179100001500276700001600291856009700307 2009 eng d00aConstrained item selection using a stochastically curtailed SPRT0 aConstrained item selection using a stochastically curtailed SPRT aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aWouda, J T1 aEggen, Theo uhttp://mail.iacat.org/content/constrained-item-selection-using-stochastically-curtailed-sprt01664nas a2200145 4500008004100000245004900041210004800090260009700138520115900235100001301394700001101407700001401418700001101432856007501443 2009 eng d00aDeveloping item variants: An empirical study0 aDeveloping item variants An empirical study aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aLarge-scale standardized test have been widely used for educational and licensure testing. In computerized adaptive testing (CAT), one of the practical concerns for maintaining large-scale assessments is to ensure adequate numbers of high-quality items that are required for item pool functioning. Developing items at specific difficulty levels and for certain areas of test plans is a wellknown challenge. The purpose of this study was to investigate strategies for varying items that can effectively generate items at targeted difficulty levels and specific test plan areas. Each variant item generation model was developed by decomposing selected source items possessing ideal measurement properties and targeting the desirable content domains. 341 variant items were generated from 72 source items. Data were collected from six pretest periods. Items were calibrated using the Rasch model. Initial results indicate that variant items showed desirable measurement properties. Additionally, compared to an average of approximately 60% of the items passing pretest criteria, an average of 84% of the variant items passed the pretest criteria. 1 aWendt, A1 aKao, S1 aGorham, J1 aWoo, A uhttp://mail.iacat.org/content/developing-item-variants-empirical-study02882nas a2200493 4500008004100000020004100041245014100082210006900223250001500292260000800307300001100315490000700326520125100333653003001584653001001614653000901624653004601633653003301679653001101712653003101723653001101754653000901765653003301774653001601807653002401823653004601847653005501893653005501948653004602003653001902049653003102068653001402099100001602113700001502129700001302144700001402157700001502171700001702186700001502203700001702218700001502235700001302250856012502263 2009 eng d a0090-5550 (Print)0090-5550 (Linking)00aDevelopment of an item bank for the assessment of depression in persons with mental illnesses and physical diseases using Rasch analysis0 aDevelopment of an item bank for the assessment of depression in  a2009/05/28 cMay a186-970 v543 aOBJECTIVE: The calibration of item banks provides the basis for computerized adaptive testing that ensures high diagnostic precision and minimizes participants' test burden. The present study aimed at developing a new item bank that allows for assessing depression in persons with mental and persons with somatic diseases. METHOD: The sample consisted of 161 participants treated for a depressive syndrome, and 206 participants with somatic illnesses (103 cardiologic, 103 otorhinolaryngologic; overall mean age = 44.1 years, SD =14.0; 44.7% women) to allow for validation of the item bank in both groups. Persons answered a pool of 182 depression items on a 5-point Likert scale. RESULTS: Evaluation of Rasch model fit (infit < 1.3), differential item functioning, dimensionality, local independence, item spread, item and person separation (>2.0), and reliability (>.80) resulted in a bank of 79 items with good psychometric properties. CONCLUSIONS: The bank provides items with a wide range of content coverage and may serve as a sound basis for computerized adaptive testing applications. It might also be useful for researchers who wish to develop new fixed-length scales for the assessment of depression in specific rehabilitation settings.10aAdaptation, Psychological10aAdult10aAged10aDepressive Disorder/*diagnosis/psychology10aDiagnosis, Computer-Assisted10aFemale10aHeart Diseases/*psychology10aHumans10aMale10aMental Disorders/*psychology10aMiddle Aged10aModels, Statistical10aOtorhinolaryngologic Diseases/*psychology10aPersonality Assessment/statistics & numerical data10aPersonality Inventory/*statistics & numerical data10aPsychometrics/statistics & numerical data10aQuestionnaires10aReproducibility of Results10aSick Role1 aForkmann, T1 aBoecker, M1 aNorra, C1 aEberle, N1 aKircher, T1 aSchauerte, P1 aMischke, K1 aWesthofen, M1 aGauggel, S1 aWirtz, M uhttp://mail.iacat.org/content/development-item-bank-assessment-depression-persons-mental-illnesses-and-physical-diseases00532nas a2200109 4500008004100000245008500041210006900126260009700195100001500292700001400307856010100321 2009 eng d00aEffect of early misfit in computerized adaptive testing on the recovery of theta0 aEffect of early misfit in computerized adaptive testing on the r aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aGuyer, R D1 aWeiss, DJ uhttp://mail.iacat.org/content/effect-early-misfit-computerized-adaptive-testing-recovery-theta-002371nas a2200217 4500008004100000020002200041245010800063210006900171250001500240260001000255300001200265490000700277520166400284100001401948700001401962700001601976700001201992700001702004700001502021856011702036 2009 Eng d a1049-8931 (Print)00aEvaluation of a computer-adaptive test for the assessment of depression (D-CAT) in clinical application0 aEvaluation of a computeradaptive test for the assessment of depr a2009/02/06 cFeb 4 a233-2360 v183 aIn the past, a German Computerized Adaptive Test, based on Item Response Theory (IRT), was developed for purposes of assessing the construct depression [Computer-adaptive test for depression (D-CAT)]. This study aims at testing the feasibility and validity of the real computer-adaptive application.The D-CAT, supplied by a bank of 64 items, was administered on personal digital assistants (PDAs) to 423 consecutive patients suffering from psychosomatic and other medical conditions (78 with depression). Items were adaptively administered until a predetermined reliability (r >/= 0.90) was attained. For validation purposes, the Hospital Anxiety and Depression Scale (HADS), the Centre for Epidemiological Studies Depression (CES-D) scale, and the Beck Depression Inventory (BDI) were administered. Another sample of 114 patients was evaluated using standardized diagnostic interviews [Composite International Diagnostic Interview (CIDI)].The D-CAT was quickly completed (mean 74 seconds), well accepted by the patients and reliable after an average administration of only six items. In 95% of the cases, 10 items or less were needed for a reliable score estimate. Correlations between the D-CAT and the HADS, CES-D, and BDI ranged between r = 0.68 and r = 0.77. The D-CAT distinguished between diagnostic groups as well as established questionnaires do.The D-CAT proved an efficient, well accepted and reliable tool. Discriminative power was comparable to other depression measures, whereby the CAT is shorter and more precise. Item usage raises questions of balancing the item selection for content in the future. Copyright (c) 2009 John Wiley & Sons, Ltd.1 aFliege, H1 aBecker, J1 aWalter, O B1 aRose, M1 aBjorner, J B1 aKlapp, B F uhttp://mail.iacat.org/content/evaluation-computer-adaptive-test-assessment-depression-d-cat-clinical-application02752nas a2200433 4500008004100000020004600041245012800087210006900215250001500284300001200299490000700311520139300318653003401711653001501745653001001760653000901770653002201779653002501801653001101826653001101837653000901848653001601857653001501873653003801888653001901926653003101945653002801976653004802004653002202052100002002074700001202094700001402106700001602120700001402136700001702150700001502167700001502182856012102197 2009 eng d a1878-5921 (Electronic)0895-4356 (Linking)00aAn evaluation of patient-reported outcomes found computerized adaptive testing was efficient in assessing stress perception0 aevaluation of patientreported outcomes found computerized adapti a2008/07/22 a278-2870 v623 aOBJECTIVES: This study aimed to develop and evaluate a first computerized adaptive test (CAT) for the measurement of stress perception (Stress-CAT), in terms of the two dimensions: exposure to stress and stress reaction. STUDY DESIGN AND SETTING: Item response theory modeling was performed using a two-parameter model (Generalized Partial Credit Model). The evaluation of the Stress-CAT comprised a simulation study and real clinical application. A total of 1,092 psychosomatic patients (N1) were studied. Two hundred simulees (N2) were generated for a simulated response data set. Then the Stress-CAT was given to n=116 inpatients, (N3) together with established stress questionnaires as validity criteria. RESULTS: The final banks included n=38 stress exposure items and n=31 stress reaction items. In the first simulation study, CAT scores could be estimated with a high measurement precision (SE<0.32; rho>0.90) using 7.0+/-2.3 (M+/-SD) stress reaction items and 11.6+/-1.7 stress exposure items. The second simulation study reanalyzed real patients data (N1) and showed an average use of items of 5.6+/-2.1 for the dimension stress reaction and 10.0+/-4.9 for the dimension stress exposure. Convergent validity showed significantly high correlations. CONCLUSIONS: The Stress-CAT is short and precise, potentially lowering the response burden of patients in clinical decision making.10a*Diagnosis, Computer-Assisted10aAdolescent10aAdult10aAged10aAged, 80 and over10aConfidence Intervals10aFemale10aHumans10aMale10aMiddle Aged10aPerception10aQuality of Health Care/*standards10aQuestionnaires10aReproducibility of Results10aSickness Impact Profile10aStress, Psychological/*diagnosis/psychology10aTreatment Outcome1 aKocalevent, R D1 aRose, M1 aBecker, J1 aWalter, O B1 aFliege, H1 aBjorner, J B1 aKleiber, D1 aKlapp, B F uhttp://mail.iacat.org/content/evaluation-patient-reported-outcomes-found-computerized-adaptive-testing-was-efficient00479nas a2200109 4500008004100000245006200041210006000103260009700163100001600260700001400276856007900290 2009 eng d00aA hybrid simulation procedure for the development of CATs0 ahybrid simulation procedure for the development of CATs aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aNydick, S W1 aWeiss, DJ uhttp://mail.iacat.org/content/hybrid-simulation-procedure-development-cats01387nas a2200241 4500008004100000020002700041245005000068210005000118250001500168300001000183490000600193520067500199653002600874653001100900653004200911653002400953653001800977653002000995653001901015100001501034700001601049856008001065 2009 eng d a1548-5951 (Electronic)00aItem response theory and clinical measurement0 aItem response theory and clinical measurement a2008/11/04 a27-480 v53 aIn this review, we examine studies that use item response theory (IRT) to explore the psychometric properties of clinical measures. Next, we consider how IRT has been used in clinical research for: scale linking, computerized adaptive testing, and differential item functioning analysis. Finally, we consider the scale properties of IRT trait scores. We conclude that there are notable differences between cognitive and clinical measures that have relevance for IRT modeling. Future research should be directed toward a better understanding of the metric of the latent trait and the psychological processes that lead to individual differences in item response behaviors.10a*Psychological Theory10aHumans10aMental Disorders/diagnosis/psychology10aPsychological Tests10aPsychometrics10aQuality of Life10aQuestionnaires1 aReise, S P1 aWaller, N G uhttp://mail.iacat.org/content/item-response-theory-and-clinical-measurement00557nas a2200121 4500008004100000245008100041210006900122260009700191100001700288700001400305700001600319856010000335 2009 eng d00aItem selection and hypothesis testing for the adaptive measurement of change0 aItem selection and hypothesis testing for the adaptive measureme aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aFinkelman, M1 aWeiss, DJ1 aKim-Kang, G uhttp://mail.iacat.org/content/item-selection-and-hypothesis-testing-adaptive-measurement-change02036nas a2200121 4500008004100000245009400041210006900135260009700204520146200301100001201763700001901775856012001794 2009 eng d00aKullback-Leibler information in multidimensional adaptive testing: theory and application0 aKullbackLeibler information in multidimensional adaptive testing aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aBuilt on multidimensional item response theory (MIRT), multidimensional adaptive testing (MAT) can, in principle, provide a promising choice to ensuring efficient estimation of each ability dimension in a multidimensional vector. Currently, two item selection procedures have been developed for MAT, one based on Fisher information embedded within a Bayesian framework, and the other powered by Kullback-Leibler (KL) information. It is well-known that in unidimensional IRT that the second derivative of KL information (also termed “global information”) is Fisher information evaluated atθ 0. This paper first generalizes the relationship between these two types of information in two ways—the analytical result is given as well as the graphical representation, to enhance interpretation and understanding. Second, a KL information index is constructed for MAT, which represents the integration of KL nformation over all of the ability dimensions. This paper further discusses how this index correlates with the item discrimination parameters. The analytical results would lay foundation for future development of item selection methods in MAT which can help equalize the item exposure rate. Finally, a simulation study is conducted to verify the above results. The connection between the item parameters, item KL information, and item exposure rate is demonstrated for empirical MAT delivered by an item bank calibrated under two-dimensional IRT.1 aWang, C1 aChang, Hua-Hua uhttp://mail.iacat.org/content/kullback-leibler-information-multidimensional-adaptive-testing-theory-and-application00579nas a2200133 4500008004100000245007700041210006900118260011100187100001000298700001400308700001400322700001100336856009800347 2009 eng d00aLimiting item exposure for target difficulty ranges in a high-stakes CAT0 aLimiting item exposure for target difficulty ranges in a highsta aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing. {PDF File, 1.1 aLi, X1 aBecker, K1 aGorham, J1 aWoo, A uhttp://mail.iacat.org/content/limiting-item-exposure-target-difficulty-ranges-high-stakes-cat03148nas a2200457 4500008004100000020004100041245015500082210006900237250001500306260000800321300001200329490000700341520174100348653002502089653001902114653002502133653003002158653001502188653003602203653001002239653002102249653003302270653001102303653001102314653000902325653001802334653001702352653001902369653001602388100001502404700001002419700001502429700002502444700001802469700001702487700001602504700001602520700001402536700001602550856012402566 2009 eng d a0962-9343 (Print)0962-9343 (Linking)00aMeasuring global physical health in children with cerebral palsy: Illustration of a multidimensional bi-factor model and computerized adaptive testing0 aMeasuring global physical health in children with cerebral palsy a2009/02/18 cApr a359-3700 v183 aPURPOSE: The purposes of this study were to apply a bi-factor model for the determination of test dimensionality and a multidimensional CAT using computer simulations of real data for the assessment of a new global physical health measure for children with cerebral palsy (CP). METHODS: Parent respondents of 306 children with cerebral palsy were recruited from four pediatric rehabilitation hospitals and outpatient clinics. We compared confirmatory factor analysis results across four models: (1) one-factor unidimensional; (2) two-factor multidimensional (MIRT); (3) bi-factor MIRT with fixed slopes; and (4) bi-factor MIRT with varied slopes. We tested whether the general and content (fatigue and pain) person score estimates could discriminate across severity and types of CP, and whether score estimates from a simulated CAT were similar to estimates based on the total item bank, and whether they correlated as expected with external measures. RESULTS: Confirmatory factor analysis suggested separate pain and fatigue sub-factors; all 37 items were retained in the analyses. From the bi-factor MIRT model with fixed slopes, the full item bank scores discriminated across levels of severity and types of CP, and compared favorably to external instruments. CAT scores based on 10- and 15-item versions accurately captured the global physical health scores. CONCLUSIONS: The bi-factor MIRT CAT application, especially the 10- and 15-item versions, yielded accurate global physical health scores that discriminated across known severity groups and types of CP, and correlated as expected with concurrent measures. The CATs have potential for collecting complex data on the physical health of children with CP in an efficient manner.10a*Computer Simulation10a*Health Status10a*Models, Statistical10aAdaptation, Psychological10aAdolescent10aCerebral Palsy/*physiopathology10aChild10aChild, Preschool10aFactor Analysis, Statistical10aFemale10aHumans10aMale10aMassachusetts10aPennsylvania10aQuestionnaires10aYoung Adult1 aHaley, S M1 aNi, P1 aDumas, H M1 aFragala-Pinkham, M A1 aHambleton, RK1 aMontpetit, K1 aBilodeau, N1 aGorton, G E1 aWatson, K1 aTucker, C A uhttp://mail.iacat.org/content/measuring-global-physical-health-children-cerebral-palsy-illustration-multidimensional-bi00545nas a2200121 4500008004100000245007000041210006900111260009700180100001200277700001900289700001500308856010000323 2009 eng d00aObtaining reliable diagnostic information through constrained CAT0 aObtaining reliable diagnostic information through constrained CA aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aWang, C1 aChang, Hua-Hua1 aDouglas, J uhttp://mail.iacat.org/content/obtaining-reliable-diagnostic-information-through-constrained-cat00539nas a2200121 4500008004100000245007800041210006900119260009700188100001500285700001200300700001100312856009400323 2009 eng d00aPractical issues concerning the application of the DINA model to CAT data0 aPractical issues concerning the application of the DINA model to aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aHuebner, A1 aWang, B1 aLee, S uhttp://mail.iacat.org/content/practical-issues-concerning-application-dina-model-cat-data02598nas a2200337 4500008004100000020004600041245012800087210006900215250001500284300000700299490000600306520149200312653003201804653002301836653002501859653003401884653001101918653001101929653000901940653002601949653003101975653002702006653001102033653001802044100001502062700001202077700001402089700001802103700001202121856012702133 2009 eng d a1477-7525 (Electronic)1477-7525 (Linking)00aReduction in patient burdens with graphical computerized adaptive testing on the ADL scale: tool development and simulation0 aReduction in patient burdens with graphical computerized adaptiv a2009/05/07 a390 v73 aBACKGROUND: The aim of this study was to verify the effectiveness and efficacy of saving time and reducing burden for patients, nurses, and even occupational therapists through computer adaptive testing (CAT). METHODS: Based on an item bank of the Barthel Index (BI) and the Frenchay Activities Index (FAI) for assessing comprehensive activities of daily living (ADL) function in stroke patients, we developed a visual basic application (VBA)-Excel CAT module, and (1) investigated whether the averaged test length via CAT is shorter than that of the traditional all-item-answered non-adaptive testing (NAT) approach through simulation, (2) illustrated the CAT multimedia on a tablet PC showing data collection and response errors of ADL clinical functional measures in stroke patients, and (3) demonstrated the quality control of endorsing scale with fit statistics to detect responding errors, which will be further immediately reconfirmed by technicians once patient ends the CAT assessment. RESULTS: The results show that endorsed items could be shorter on CAT (M = 13.42) than on NAT (M = 23) at 41.64% efficiency in test length. However, averaged ability estimations reveal insignificant differences between CAT and NAT. CONCLUSION: This study found that mobile nursing services, placed at the bedsides of patients could, through the programmed VBA-Excel CAT module, reduce the burden to patients and save time, more so than the traditional NAT paper-and-pencil testing appraisals.10a*Activities of Daily Living10a*Computer Graphics10a*Computer Simulation10a*Diagnosis, Computer-Assisted10aFemale10aHumans10aMale10aPoint-of-Care Systems10aReproducibility of Results10aStroke/*rehabilitation10aTaiwan10aUnited States1 aChien, T W1 aWu, H M1 aWang, W-C1 aCastillo, R V1 aChou, W uhttp://mail.iacat.org/content/reduction-patient-burdens-graphical-computerized-adaptive-testing-adl-scale-tool-development00558nas a2200109 4500008003900000245009400039210006900133260009800202100001500300700001400315856011900329 2009 d00aTermination criteria in computerized adaptive tests: Variable-length CATs are not biased.0 aTermination criteria in computerized adaptive tests Variableleng a D. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aBabcock, B1 aWeiss, DJ uhttp://mail.iacat.org/content/termination-criteria-computerized-adaptive-tests-variable-length-cats-are-not-biased00376nas a2200121 4500008004100000245004600041210004600087300001000133490000800143100001600151700001400167856007300181 2008 eng d00aAdaptive measurement of individual change0 aAdaptive measurement of individual change a49-580 v2161 aKim-Kang, G1 aWeiss, DJ uhttp://mail.iacat.org/content/adaptive-measurement-individual-change01225nas a2200133 4500008003900000245008800039210006900127260000900196300001400205520072100219100002000940700002000960856011100980 2008 d00aAn Automated Decision System for Computer Adaptive Testing Using Genetic Algorithms0 aAutomated Decision System for Computer Adaptive Testing Using Ge bIEEE a655–6603 aThis paper proposes an approach to solve the triangle decision tree problem for computer adaptive testing (CAT) using genetic algorithms (GAs). In this approach, item response theory (IRT) parameters composed of discrimination, difficulty, and guess are firstly obtained and stored in an item bank. Then a fitness function, which is based on IRT parameters, of GAs for obtaining an optimal solution is set up. Finally, the GAs is applied to the parameters of the item bank so that an optimal decision tree is generated. Based on a six-level triangle-decision tree for examination items, the experimental results show that the optimal decision tree can be generated correctly when compared with the standard patterns.1 aPhankokkruad, M1 aWoraratpanya, K uhttp://mail.iacat.org/content/automated-decision-system-computer-adaptive-testing-using-genetic-algorithms00582nas a2200145 4500008004100000245012000041210006900161300001400230490000700244100001400251700001400265700001900279700001800298856012000316 2008 eng d00aComputerized adaptive testing for patients with knee inpairments produced valid and responsive measures of function0 aComputerized adaptive testing for patients with knee inpairments a1113-11240 v611 aHart, D L1 aWang, Y-C1 aStratford, P W1 aMioduski, J E uhttp://mail.iacat.org/content/computerized-adaptive-testing-patients-knee-inpairments-produced-valid-and-responsive02391nas a2200205 4500008004100000020001400041245008800055210006900143300001400212490000700226520173800233100001401971700001401985700002001999700001702019700001202036700001602048700001502064856010602079 2008 eng d a1520-639400aFunctioning and validity of a computerized adaptive test to measure anxiety (A CAT)0 aFunctioning and validity of a computerized adaptive test to meas aE182-E1940 v253 aBackground: The aim of this study was to evaluate the Computerized Adaptive Test to measure anxiety (A-CAT), a patient-reported outcome questionnaire that uses computerized adaptive testing to measure anxiety. Methods: The A-CAT builds on an item bank of 50 items that has been built using conventional item analyses and item response theory analyses. The A-CAT was administered on Personal Digital Assistants to n=357 patients diagnosed and treated at the department of Psychosomatic Medicine and Psychotherapy, Charité Berlin, Germany. For validation purposes, two subgroups of patients (n=110 and 125) answered the A-CAT along with established anxiety and depression questionnaires. Results: The A-CAT was fast to complete (on average in 2 min, 38 s) and a precise item response theory based CAT score (reliability>.9) could be estimated after 4–41 items. On average, the CAT displayed 6 items (SD=4.2). Convergent validity of the A-CAT was supported by correlations to existing tools (Hospital Anxiety and Depression Scale-A, Beck Anxiety Inventory, Berliner Stimmungs-Fragebogen A/D, and State Trait Anxiety Inventory: r=.56–.66); discriminant validity between diagnostic groups was higher for the A-CAT than for other anxiety measures. Conclusions: The German A-CAT is an efficient, reliable, and valid tool for assessing anxiety in patients suffering from anxiety disorders and other conditions with significant potential for initial assessment and long-term treatment monitoring. Future research directions are to explore content balancing of the item selection algorithm of the CAT, to norm the tool to a healthy sample, and to develop practical cutoff scores. Depression and Anxiety, 2008. © 2008 Wiley-Liss, Inc.1 aBecker, J1 aFliege, H1 aKocalevent, R D1 aBjorner, J B1 aRose, M1 aWalter, O B1 aKlapp, B F uhttp://mail.iacat.org/content/functioning-and-validity-computerized-adaptive-test-measure-anxiety-cat00463nas a2200121 4500008004100000245008400041210006900125300000900194490000700203100001300210700001400223856010400237 2008 eng d00aInvestigating item exposure control on the fly in computerized adaptive testing0 aInvestigating item exposure control on the fly in computerized a a1-320 v551 aWu, M -L1 aChen, S-Y uhttp://mail.iacat.org/content/investigating-item-exposure-control-fly-computerized-adaptive-testing00476nas a2200133 4500008003900000245007300039210006900112300001200181490000700193100001500200700001900215700001600234856009200250 2008 d00aA monte carlo approach for adaptive testing with content constraints0 amonte carlo approach for adaptive testing with content constrain a431-4460 v321 aBelov, D I1 aArmstrong, R D1 aWeissman, A uhttp://mail.iacat.org/content/monte-carlo-approach-adaptive-testing-content-constraints01234nas a2200145 4500008003900000245007300039210006900112300001200181490000700193520076500200100002100965700002500986700002401011856005301035 2008 d00aA Monte Carlo Approach for Adaptive Testing With Content Constraints0 aMonte Carlo Approach for Adaptive Testing With Content Constrain a431-4460 v323 a

This article presents a new algorithm for computerized adaptive testing (CAT) when content constraints are present. The algorithm is based on shadow CAT methodology to meet content constraints but applies Monte Carlo methods and provides the following advantages over shadow CAT: (a) lower maximum item exposure rates, (b) higher utilization of the item pool, and (c) more robust ability estimates. Computer simulations with Law School Admission Test items demonstrated that the new algorithm (a) produces similar ability estimates as shadow CAT but with half the maximum item exposure rate and 100% pool utilization and (b) produces more robust estimates when a high- (or low-) ability examinee performs poorly (or well) at the beginning of the test.

1 aBelov, Dmitry, I1 aArmstrong, Ronald, D1 aWeissman, Alexander uhttp://apm.sagepub.com/content/32/6/431.abstract00470nas a2200121 4500008004100000245008100041210006900122300001200191490001100203100001600214700001500230856010300245 2008 eng d00aTransitioning from fixed-length questionnaires to computer-adaptive versions0 aTransitioning from fixedlength questionnaires to computeradaptiv a22–280 v216(1)1 aWalter, O B1 aHolling, H uhttp://mail.iacat.org/content/transitioning-fixed-length-questionnaires-computer-adaptive-versions03158nas a2200493 4500008004100000020002200041245008900063210006900152250001500221260000800236300001000244490000700254520169600261653003401957653002001991653001502011653001002026653000902036653002602045653003202071653003102103653001102134653001102145653000902156653003202165653001602197653002902213653004402242653002902286653003102315653003102346653001702377100001702394700001402411700001602425700001302441700001702454700002202471700001702493700001402510700001402524700001702538856010902555 2008 eng d a1075-2730 (Print)00aUsing computerized adaptive testing to reduce the burden of mental health assessment0 aUsing computerized adaptive testing to reduce the burden of ment a2008/04/02 cApr a361-80 v593 aOBJECTIVE: This study investigated the combination of item response theory and computerized adaptive testing (CAT) for psychiatric measurement as a means of reducing the burden of research and clinical assessments. METHODS: Data were from 800 participants in outpatient treatment for a mood or anxiety disorder; they completed 616 items of the 626-item Mood and Anxiety Spectrum Scales (MASS) at two times. The first administration was used to design and evaluate a CAT version of the MASS by using post hoc simulation. The second confirmed the functioning of CAT in live testing. RESULTS: Tests of competing models based on item response theory supported the scale's bifactor structure, consisting of a primary dimension and four group factors (mood, panic-agoraphobia, obsessive-compulsive, and social phobia). Both simulated and live CAT showed a 95% average reduction (585 items) in items administered (24 and 30 items, respectively) compared with administration of the full MASS. The correlation between scores on the full MASS and the CAT version was .93. For the mood disorder subscale, differences in scores between two groups of depressed patients--one with bipolar disorder and one without--on the full scale and on the CAT showed effect sizes of .63 (p<.003) and 1.19 (p<.001) standard deviation units, respectively, indicating better discriminant validity for CAT. CONCLUSIONS: Instead of using small fixed-length tests, clinicians can create item banks with a large item pool, and a small set of the items most relevant for a given individual can be administered with no loss of information, yielding a dramatic reduction in administration time and patient and clinician burden.10a*Diagnosis, Computer-Assisted10a*Questionnaires10aAdolescent10aAdult10aAged10aAgoraphobia/diagnosis10aAnxiety Disorders/diagnosis10aBipolar Disorder/diagnosis10aFemale10aHumans10aMale10aMental Disorders/*diagnosis10aMiddle Aged10aMood Disorders/diagnosis10aObsessive-Compulsive Disorder/diagnosis10aPanic Disorder/diagnosis10aPhobic Disorders/diagnosis10aReproducibility of Results10aTime Factors1 aGibbons, R D1 aWeiss, DJ1 aKupfer, D J1 aFrank, E1 aFagiolini, A1 aGrochocinski, V J1 aBhaumik, D K1 aStover, A1 aBock, R D1 aImmekus, J C uhttp://mail.iacat.org/content/using-computerized-adaptive-testing-reduce-burden-mental-health-assessment02411nas a2200193 4500008004100000020002200041245011700063210006900180250001500249300001100264490000600275520172700281100001502008700001702023700001602040700001802056700001802074856012502092 2008 eng d a1740-7745 (Print)00aUsing item banks to construct measures of patient reported outcomes in clinical trials: investigator perceptions0 aUsing item banks to construct measures of patient reported outco a2008/11/26 a575-860 v53 aBACKGROUND: Item response theory (IRT) promises more sensitive and efficient measurement of patient-reported outcomes (PROs) than traditional approaches; however, the selection and use of PRO measures from IRT-based item banks differ from current methods of using PRO measures. PURPOSE: To anticipate barriers to the adoption of IRT item banks into clinical trials. METHODS: We conducted semistructured telephone or in-person interviews with 42 clinical researchers who published results from clinical trials in the Journal of the American Medical Association, the New England Journal of Medicine, or other leading clinical journals from July 2005 through May 2006. Interviews included a brief tutorial on IRT item banks. RESULTS: After the tutorial, 39 of 42 participants understood the novel products available from an IRT item bank, namely customized short forms and computerized adaptive testing. Most participants (38/42) thought that item banks could be useful in their clinical trials, but they mentioned several potential barriers to adoption, including economic and logistical constraints, concerns about whether item banks are better than current PRO measures, concerns about how to convince study personnel or statisticians to use item banks, concerns about FDA or sponsor acceptance, and the lack of availability of item banks validated in specific disease populations. LIMITATIONS: Selection bias might have led to more positive responses to the concept of item banks in clinical trials. CONCLUSIONS: Clinical investigators are open to a new method of PRO measurement offered in IRT item banks, but bank developers must address investigator and stakeholder concerns before widespread adoption can be expected.1 aFlynn, K E1 aDombeck, C B1 aDeWitt, E M1 aSchulman, K A1 aWeinfurt, K P uhttp://mail.iacat.org/content/using-item-banks-construct-measures-patient-reported-outcomes-clinical-trials-investigator01940nas a2200157 4500008004100000245011600041210006900157300001200226490000700238520135500245100001601600700001201616700001601628700001401644856012401658 2008 eng d00aUtilizing Rasch measurement models to develop a computer adaptive self-report of walking, climbing, and running0 aUtilizing Rasch measurement models to develop a computer adaptiv a458-4670 v303 aPurpose.The purpose of this paper is to show how the Rasch model can be used to develop a computer adaptive self-report of walking, climbing, and running.Method.Our instrument development work on the walking/climbing/running construct of the ICF Activity Measure was used to show how to develop a computer adaptive test (CAT). Fit of the items to the Rasch model and validation of the item difficulty hierarchy was accomplished using Winsteps software. Standard error was used as a stopping rule for the CAT. Finally, person abilities were connected to items difficulties using Rasch analysis ‘maps’.Results.All but the walking one mile item fit the Rasch measurement model. A CAT was developed which selectively presented items based on the last calibrated person ability measure and was designed to stop when standard error decreased to a pre-set criterion. Finally, person ability measures were connected to the ability to perform specific walking/climbing/running activities using Rasch maps.Conclusions.Rasch measurement models can be useful in developing CAT measures for rehabilitation and disability. In addition to CATs reducing respondent burden, the connection of person measures to item difficulties may be important for the clinical interpretation of measures.Read More: http://informahealthcare.com/doi/abs/10.1080/096382807016173171 aVelozo, C A1 aWang, Y1 aLehman, L A1 aWang, J H uhttp://mail.iacat.org/content/utilizing-rasch-measurement-models-develop-computer-adaptive-self-report-walking-climbing00523nas a2200109 4500008004100000245007700041210006900118260009700187100001500284700001400299856010000313 2007 eng d00aBundle models for computerized adaptive testing in e-learning assessment0 aBundle models for computerized adaptive testing in elearning ass aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aScalise, K1 aWilson, M uhttp://mail.iacat.org/content/bundle-models-computerized-adaptive-testing-e-learning-assessment00574nas a2200109 4500008004100000245010200041210006900143260009700212100001600309700001400325856012500339 2007 eng d00aComparison of computerized adaptive testing and classical methods for measuring individual change0 aComparison of computerized adaptive testing and classical method aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aKim-Kang, G1 aWeiss, DJ uhttp://mail.iacat.org/content/comparison-computerized-adaptive-testing-and-classical-methods-measuring-individual-change00474nas a2200109 4500008004100000245005800041210005800099260009700157100001400254700001700268856007900285 2007 eng d00aComputerized adaptive testing with the bifactor model0 aComputerized adaptive testing with the bifactor model aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aWeiss, DJ1 aGibbons, R D uhttp://mail.iacat.org/content/computerized-adaptive-testing-bifactor-model00600nas a2200169 4500008004100000245009100041210006900132300001200201490000700213100001600220700001400236700001700250700001400267700001500281700001200296856012200308 2007 eng d00aDevelopment and evaluation of a computer adaptive test for “Anxiety” (Anxiety-CAT)0 aDevelopment and evaluation of a computer adaptive test for Anxie a143-1550 v161 aWalter, O B1 aBecker, J1 aBjorner, J B1 aFliege, H1 aKlapp, B F1 aRose, M uhttp://mail.iacat.org/content/development-and-evaluation-computer-adaptive-test-%E2%80%9Canxiety%E2%80%9D-anxiety-cat02413nas a2200361 4500008004500000020001400045245011100059210006900170300001200239490000700251520135900258653001601617653002001633653001301653653002401666653002501690653001101715653001401726653001301740653001801753653002701771653001001798653001101808100001501819700001201834700001601846700001201862700001601874700001301890700001301903700001401916856012101930 2007 Engldsh  a1057-924900aThe initial development of an item bank to assess and screen for psychological distress in cancer patients0 ainitial development of an item bank to assess and screen for psy a724-7320 v163 aPsychological distress is a common problem among cancer patients. Despite the large number of instruments that have been developed to assess distress, their utility remains disappointing. This study aimed to use Rasch models to develop an item-bank which would provide the basis for better means of assessing psychological distress in cancer patients. An item bank was developed from eight psychological distress questionnaires using Rasch analysis to link common items. Items from the questionnaires were added iteratively with common items as anchor points and misfitting items (infit mean square > 1.3) removed, and unidimensionality assessed. A total of 4914 patients completed the questionnaires providing an initial pool of 83 items. Twenty items were removed resulting in a final pool of 63 items. Good fit was demonstrated and no additional factor structure was evident from the residuals. However, there was little overlap between item locations and person measures, since items mainly targeted higher levels of distress. The Rasch analysis allowed items to be pooled and generated a unidimensional instrument for measuring psychological distress in cancer patients. Additional items are required to more accurately assess patients across the whole continuum of psychological distress. (PsycINFO Database Record (c) 2007 APA ) (journal abstract)10a3293 Cancer10acancer patients10aDistress10ainitial development10aItem Response Theory10aModels10aNeoplasms10aPatients10aPsychological10apsychological distress10aRasch10aStress1 aSmith, A B1 aRush, R1 aVelikova, G1 aWall, L1 aWright, E P1 aStark, D1 aSelby, P1 aSharpe, M uhttp://mail.iacat.org/content/initial-development-item-bank-assess-and-screen-psychological-distress-cancer-patients00515nas a2200109 4500008004100000245007300041210006900114260010000183100001600283700001300299856009300312 2007 eng d00aInvestigating CAT designs to achieve comparability with a paper test0 aInvestigating CAT designs to achieve comparability with a paper  aIn D. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aThompson, T1 aWay, W D uhttp://mail.iacat.org/content/investigating-cat-designs-achieve-comparability-paper-test01310nas a2200121 4500008003900000245007300039210006900112300001000181490000700191520091400198100002401112856005201136 2007 d00aMutual Information Item Selection in Adaptive Classification Testing0 aMutual Information Item Selection in Adaptive Classification Tes a41-580 v673 a

A general approach for item selection in adaptive multiple-category classification tests is provided. The approach uses mutual information (MI), a special case of the Kullback-Leibler distance, or relative entropy. MI works efficiently with the sequential probability ratio test and alleviates the difficulties encountered with using other local- and global-information measures in the multiple-category classification setting. Results from simulation studies using three item selection methods, Fisher information (FI), posterior-weighted FI (FIP), and MI, are provided for an adaptive four-category classification test. Both across and within the four classification categories, it is shown that in general, MI item selection classifies the highest proportion of examinees correctly and yields the shortest test lengths. The next best performance is observed for FIP item selection, followed by FI.

1 aWeissman, Alexander uhttp://epm.sagepub.com/content/67/1/41.abstract02745nas a2200541 4500008004100000020002200041245017000063210006900233250001500302260000800317300001100325490000700336520116200343653001901505653002501524653002101549653002101570653001501591653001001606653000901616653001601625653002301641653003201664653001101696653001101707653000901718653001601727653004601743653001801789653002901807653001801836100001501854700001401869700001701883700001301900700001501913700001601928700001501944700001701959700001401976700001801990700001102008700001602019700001502035700001302050700001302063856012702076 2007 eng d a0025-7079 (Print)00aPsychometric evaluation and calibration of health-related quality of life item banks: plans for the Patient-Reported Outcomes Measurement Information System (PROMIS)0 aPsychometric evaluation and calibration of healthrelated quality a2007/04/20 cMay aS22-310 v453 aBACKGROUND: The construction and evaluation of item banks to measure unidimensional constructs of health-related quality of life (HRQOL) is a fundamental objective of the Patient-Reported Outcomes Measurement Information System (PROMIS) project. OBJECTIVES: Item banks will be used as the foundation for developing short-form instruments and enabling computerized adaptive testing. The PROMIS Steering Committee selected 5 HRQOL domains for initial focus: physical functioning, fatigue, pain, emotional distress, and social role participation. This report provides an overview of the methods used in the PROMIS item analyses and proposed calibration of item banks. ANALYSES: Analyses include evaluation of data quality (eg, logic and range checking, spread of response distribution within an item), descriptive statistics (eg, frequencies, means), item response theory model assumptions (unidimensionality, local independence, monotonicity), model fit, differential item functioning, and item calibration for banking. RECOMMENDATIONS: Summarized are key analytic issues; recommendations are provided for future evaluations of item banks in HRQOL assessment.10a*Health Status10a*Information Systems10a*Quality of Life10a*Self Disclosure10aAdolescent10aAdult10aAged10aCalibration10aDatabases as Topic10aEvaluation Studies as Topic10aFemale10aHumans10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods10aPsychometrics10aQuestionnaires/standards10aUnited States1 aReeve, B B1 aHays, R D1 aBjorner, J B1 aCook, KF1 aCrane, P K1 aTeresi, J A1 aThissen, D1 aRevicki, D A1 aWeiss, DJ1 aHambleton, RK1 aLiu, H1 aGershon, RC1 aReise, S P1 aLai, J S1 aCella, D uhttp://mail.iacat.org/content/psychometric-evaluation-and-calibration-health-related-quality-life-item-banks-plans-patient00421nas a2200121 4500008004100000245005700041210005500098260002200153100001600175700001300191700001900204856007600223 2006 eng d00aA comparison of online calibration methods for a CAT0 acomparison of online calibration methods for a CAT aSan Francisco, CA1 aMorgan, D L1 aWay, W D1 aAugemberg, K E uhttp://mail.iacat.org/content/comparison-online-calibration-methods-cat03167nas a2200361 4500008004100000020002200041245013600063210006900199250001500268260000800283300001200291490000700303520206800310653001502378653002402393653002102417653001002438653000902448653002902457653003402486653002402520653001102544653001102555653001302566653000902579653001602588100001602604700001302620700002302633700001202656700001102668856012602679 2006 eng d a0962-9343 (Print)00aComputerized adaptive testing of diabetes impact: a feasibility study of Hispanics and non-Hispanics in an active clinic population0 aComputerized adaptive testing of diabetes impact a feasibility s a2006/10/13 cNov a1503-180 v153 aBACKGROUND: Diabetes is a leading cause of death and disability in the US and is twice as common among Hispanic Americans as non-Hispanics. The societal costs of diabetes provide an impetus for developing tools that can improve patient care and delay or prevent diabetes complications. METHODS: We implemented a feasibility study of a Computerized Adaptive Test (CAT) to measure diabetes impact using a sample of 103 English- and 97 Spanish-speaking patients (mean age = 56.5, 66.5% female) in a community medical center with a high proportion of minority patients (28% African-American). The 37 items of the Diabetes Impact Survey were translated using forward-backward translation and cognitive debriefing. Participants were randomized to receive either the full-length tool or the Diabetes-CAT first, in the patient's native language. RESULTS: The number of items and the amount of time to complete the survey for the CAT was reduced to one-sixth the amount for the full-length tool in both languages, across disease severity. Confirmatory Factor Analysis confirmed that the Diabetes Impact Survey is unidimensional. The Diabetes-CAT demonstrated acceptable internal consistency reliability, construct validity, and discriminant validity in the overall sample, although subgroup analyses suggested that the English sample data evidenced higher levels of reliability and validity than the Spanish sample and issues with discriminant validity in the Spanish sample. Differential Item Function analysis revealed differences in responses tendencies by language group in 3 of the 37 items. Participant interviews suggested that the Spanish-speaking patients generally preferred the paper survey to the computer-assisted tool, and were twice as likely to experience difficulties understanding the items. CONCLUSIONS: While the Diabetes-CAT demonstrated clear advantages in reducing respondent burden as compared to the full-length tool, simplifying the item bank will be necessary for enhancing the feasibility of the Diabetes-CAT for use with low literacy patients.10a*Computers10a*Hispanic Americans10a*Quality of Life10aAdult10aAged10aData Collection/*methods10aDiabetes Mellitus/*psychology10aFeasibility Studies10aFemale10aHumans10aLanguage10aMale10aMiddle Aged1 aSchwartz, C1 aWelch, G1 aSantiago-Kelley, P1 aBode, R1 aSun, X uhttp://mail.iacat.org/content/computerized-adaptive-testing-diabetes-impact-feasibility-study-hispanics-and-non-hispanics00536nas a2200121 4500008004100000245011700041210006900158260001800227100001300245700001900258700001400277856012300291 2006 eng d00aConstraints-weighted information method for item selection of severely constrained computerized adaptive testing0 aConstraintsweighted information method for item selection of sev aSan Francisco1 aCheng, Y1 aChang, Hua-Hua1 aWang, X B uhttp://mail.iacat.org/content/constraints-weighted-information-method-item-selection-severely-constrained-computerized02133nas a2200181 4500008004100000020001300041245013400054210006900188300001200257490000700269520147700276100001601753700001501769700001401784700001601798700001401814856012301828 2006 eng d a0895435600aAn evaluation of a patient-reported outcomes found computerized adaptive testing was efficient in assessing osteoarthritis impact0 aevaluation of a patientreported outcomes found computerized adap a715-7230 v593 aBACKGROUND AND OBJECTIVES: Evaluate a patient-reported outcomes questionnaire that uses computerized adaptive testing (CAT) to measure the impact of osteoarthritis (OA) on functioning and well-being. MATERIALS AND METHODS: OA patients completed 37 questions about the impact of OA on physical, social and role functioning, emotional well-being, and vitality. Questionnaire responses were calibrated and scored using item response theory, and two scores were estimated: a Total-OA score based on patients' responses to all 37 questions, and a simulated CAT-OA score where the computer selected and scored the five most informative questions for each patient. Agreement between Total-OA and CAT-OA scores was assessed using correlations. Discriminant validity of Total-OA and CAT-OA scores was assessed with analysis of variance. Criterion measures included OA pain and severity, patient global assessment, and missed work days. RESULTS: Simulated CAT-OA and Total-OA scores correlated highly (r = 0.96). Both Total-OA and simulated CAT-OA scores discriminated significantly between patients differing on the criterion measures. F-statistics across criterion measures ranged from 39.0 (P < .001) to 225.1 (P < .001) for the Total-OA score, and from 40.5 (P < .001) to 221.5 (P < .001) for the simulated CAT-OA score. CONCLUSIONS: CAT methods produce valid and precise estimates of the impact of OA on functioning and well-being with significant reduction in response burden.1 aKosinski, M1 aBjorner, J1 aWarejr, J1 aSullivan, E1 aStraus, W uhttp://mail.iacat.org/content/evaluation-patient-reported-outcomes-found-computerized-adaptive-testing-was-efficient-001356nas a2200121 4500008003900000245010500039210006900144300001000213490000700223520092800230100002401158856005201182 2006 d00aA Feedback Control Strategy for Enhancing Item Selection Efficiency in Computerized Adaptive Testing0 aFeedback Control Strategy for Enhancing Item Selection Efficienc a84-990 v303 a

A computerized adaptive test (CAT) may be modeled as a closed-loop system, where item selection is influenced by trait level (θ) estimation and vice versa. When discrepancies exist between an examinee's estimated and true θ levels, nonoptimal item selection is a likely result. Nevertheless, examinee response behavior consistent with optimal item selection can be predicted using item response theory (IRT), without knowledge of an examinee's true θ level, yielding a specific reference point for applying an internal correcting or feedback control mechanism. Incorporating such a mechanism in a CAT is shown to be an effective strategy for increasing item selection efficiency. Results from simulation studies using maximum likelihood (ML) and modal a posteriori (MAP) trait-level estimation and Fisher information (FI) and Fisher interval information (FII) item selection are provided.

1 aWeissman, Alexander uhttp://apm.sagepub.com/content/30/2/84.abstract00395nas a2200109 4500008003900000245007400039210007200113300001000185490000600195100001800201856006600219 2006 d00aSequential Computerized Mastery Tests—Three Simulation Studies0 aSequential Computerized Mastery Tests†Three Simulation Studies a41-550 v61 aWiberg, Marie uhttp://www.tandfonline.com/doi/abs/10.1207/s15327574ijt0601_300596nas a2200145 4500008004100000245013800041210006900179300001200248490000700260100001200267700001600279700001500295700001700310856012300327 2006 eng d00aSimulated computerized adaptive test for patients with lumbar spine impairments was efficient and produced valid measures of function0 aSimulated computerized adaptive test for patients with lumbar sp a947-9560 v591 aHart, D1 aMioduski, J1 aWerenke, M1 aStratford, P uhttp://mail.iacat.org/content/simulated-computerized-adaptive-test-patients-lumbar-spine-impairments-was-efficient-and02112nas a2200229 4500008004100000245013800041210006900179300001400248490000700262520127000269653003101539653003401570653002501604653001701629653001901646653002401665100001401689700001801703700001701721700001901738856012501757 2006 eng d00aSimulated computerized adaptive test for patients with lumbar spine impairments was efficient and produced valid measures of function0 aSimulated computerized adaptive test for patients with lumbar sp a947–9560 v593 aObjective: To equate physical functioning (PF) items with Back Pain Functional Scale (BPFS) items, develop a computerized adaptive test (CAT) designed to assess lumbar spine functional status (LFS) in people with lumbar spine impairments, and compare discriminant validity of LFS measures (qIRT) generated using all items analyzed with a rating scale Item Response Theory model (RSM) and measures generated using the simulated CAT (qCAT). Methods: We performed a secondary analysis of retrospective intake rehabilitation data. Results: Unidimensionality and local independence of 25 BPFS and PF items were supported. Differential item functioning was negligible for levels of symptom acuity, gender, age, and surgical history. The RSM fit the data well. A lumbar spine specific CAT was developed that was 72% more efficient than using all 25 items to estimate LFS measures. qIRT and qCAT measures did not discriminate patients by symptom acuity, age, or gender, but discriminated patients by surgical history in similar clinically logical ways. qCAT measures were as precise as qIRT measures. Conclusion: A body part specific simulated CAT developed from an LFS item bank was efficient and produced precise measures of LFS without eroding discriminant validity.10aBack Pain Functional Scale10acomputerized adaptive testing10aItem Response Theory10aLumbar spine10aRehabilitation10aTrue-score equating1 aHart, D L1 aMioduski, J E1 aWerneke, M W1 aStratford, P W uhttp://mail.iacat.org/content/simulated-computerized-adaptive-test-patients-lumbar-spine-impairments-was-efficient-and-000538nas a2200169 4500008004100000245006700041210006300108300001600171490000700187100001400194700001400208700001600222700001700238700001500255700001200270856008600282 2005 eng d00aDevelopment of a computer-adaptive test for depression (D-CAT)0 aDevelopment of a computeradaptive test for depression DCAT a2277–22910 v141 aFliege, H1 aBecker, J1 aWalter, O B1 aBjorner, J B1 aKlapp, B F1 aRose, M uhttp://mail.iacat.org/content/development-computer-adaptive-test-depression-d-cat00560nas a2200145 4500008003900000245011100039210006900150300001000219490000700229100001400236700001400250700001800264700001700282856011500299 2005 d00aItem response theory in computer adaptive testing: implications for outcomes measurement in rehabilitation0 aItem response theory in computer adaptive testing implications f a71-780 v501 aWare, J E1 aGandek, B1 aSinclair, S J1 aBjorner, J B uhttp://mail.iacat.org/content/item-response-theory-computer-adaptive-testing-implications-outcomes-measurement10202nas a2200553 4500008004100000245016300041210006900204300001400273490000700287520862500294653001808919653003208937100001608969700001608985700001409001700001609015700001409031700001509045700001609060700001409076700001509090700001509105700001409120700001709134700001709151700001709168700001609185700001709201700001609218700001509234700001609249700001709265700002309282700001609305700002209321700001609343700001609359700001709375700001309392700001509405700001309420700001609433700001209449700001409461700001609475700002009491700001209511856012509523 2005 eng d00aToward efficient and comprehensive measurement of the alcohol problems continuum in college students: The Brief Young Adult Alcohol Consequences Questionnaire0 aToward efficient and comprehensive measurement of the alcohol pr a1180-11890 v293 aBackground: Although a number of measures of alcohol problems in college students have been studied, the psychometric development and validation of these scales have been limited, for the most part, to methods based on classical test theory. In this study, we conducted analyses based on item response theory to select a set of items for measuring the alcohol problem severity continuum in college students that balances comprehensiveness and efficiency and is free from significant gender bias., Method: We conducted Rasch model analyses of responses to the 48-item Young Adult Alcohol Consequences Questionnaire by 164 male and 176 female college students who drank on at least a weekly basis. An iterative process using item fit statistics, item severities, item discrimination parameters, model residuals, and analysis of differential item functioning by gender was used to pare the items down to those that best fit a Rasch model and that were most efficient in discriminating among levels of alcohol problems in the sample., Results: The process of iterative Rasch model analyses resulted in a final 24-item scale with the data fitting the unidimensional Rasch model very well. The scale showed excellent distributional properties, had items adequately matched to the severity of alcohol problems in the sample, covered a full range of problem severity, and appeared highly efficient in retaining all of the meaningful variance captured by the original set of 48 items., Conclusions: The use of Rasch model analyses to inform item selection produced a final scale that, in both its comprehensiveness and its efficiency, should be a useful tool for researchers studying alcohol problems in college students. To aid interpretation of raw scores, examples of the types of alcohol problems that are likely to be experienced across a range of selected scores are provided., (C)2005Research Society on AlcoholismAn important, sometimes controversial feature of all psychological phenomena is whether they are categorical or dimensional. A conceptual and psychometric framework is described for distinguishing whether the latent structure behind manifest categories (e.g., psychiatric diagnoses, attitude groups, or stages of development) is category-like or dimension-like. Being dimension-like requires (a) within-category heterogeneity and (b) between-category quantitative differences. Being category-like requires (a) within-category homogeneity and (b) between-category qualitative differences. The relation between this classification and abrupt versus smooth differences is discussed. Hybrid structures are possible. Being category-like is itself a matter of degree; the authors offer a formalized framework to determine this degree. Empirical applications to personality disorders, attitudes toward capital punishment, and stages of cognitive development illustrate the approach., (C) 2005 by the American Psychological AssociationThe authors conducted Rasch model ( G. Rasch, 1960) analyses of items from the Young Adult Alcohol Problems Screening Test (YAAPST; S. C. Hurlbut & K. J. Sher, 1992) to examine the relative severity and ordering of alcohol problems in 806 college students. Items appeared to measure a single dimension of alcohol problem severity, covering a broad range of the latent continuum. Items fit the Rasch model well, with less severe symptoms reliably preceding more severe symptoms in a potential progression toward increasing levels of problem severity. However, certain items did not index problem severity consistently across demographic subgroups. A shortened, alternative version of the YAAPST is proposed, and a norm table is provided that allows for a linking of total YAAPST scores to expected symptom expression., (C) 2004 by the American Psychological AssociationA didactic on latent growth curve modeling for ordinal outcomes is presented. The conceptual aspects of modeling growth with ordinal variables and the notion of threshold invariance are illustrated graphically using a hypothetical example. The ordinal growth model is described in terms of 3 nested models: (a) multivariate normality of the underlying continuous latent variables (yt) and its relationship with the observed ordinal response pattern (Yt), (b) threshold invariance over time, and (c) growth model for the continuous latent variable on a common scale. Algebraic implications of the model restrictions are derived, and practical aspects of fitting ordinal growth models are discussed with the help of an empirical example and Mx script ( M. C. Neale, S. M. Boker, G. Xie, & H. H. Maes, 1999). The necessary conditions for the identification of growth models with ordinal data and the methodological implications of the model of threshold invariance are discussed., (C) 2004 by the American Psychological AssociationRecent research points toward the viability of conceptualizing alcohol problems as arrayed along a continuum. Nevertheless, modern statistical techniques designed to scale multiple problems along a continuum (latent trait modeling; LTM) have rarely been applied to alcohol problems. This study applies LTM methods to data on 110 problems reported during in-person interviews of 1,348 middle-aged men (mean age = 43) from the general population. The results revealed a continuum of severity linking the 110 problems, ranging from heavy and abusive drinking, through tolerance and withdrawal, to serious complications of alcoholism. These results indicate that alcohol problems can be arrayed along a dimension of severity and emphasize the relevance of LTM to informing the conceptualization and assessment of alcohol problems., (C) 2004 by the American Psychological AssociationItem response theory (IRT) is supplanting classical test theory as the basis for measures development. This study demonstrated the utility of IRT for evaluating DSM-IV diagnostic criteria. Data on alcohol, cannabis, and cocaine symptoms from 372 adult clinical participants interviewed with the Composite International Diagnostic Interview-Expanded Substance Abuse Module (CIDI-SAM) were analyzed with Mplus ( B. Muthen & L. Muthen, 1998) and MULTILOG ( D. Thissen, 1991) software. Tolerance and legal problems criteria were dropped because of poor fit with a unidimensional model. Item response curves, test information curves, and testing of variously constrained models suggested that DSM-IV criteria in the CIDI-SAM discriminate between only impaired and less impaired cases and may not be useful to scale case severity. IRT can be used to study the construct validity of DSM-IV diagnoses and to identify diagnostic criteria with poor performance., (C) 2004 by the American Psychological AssociationThis study examined the psychometric characteristics of an index of substance use involvement using item response theory. The sample consisted of 292 men and 140 women who qualified for a Diagnostic and Statistical Manual of Mental Disorders (3rd ed., rev.; American Psychiatric Association, 1987) substance use disorder (SUD) diagnosis and 293 men and 445 women who did not qualify for a SUD diagnosis. The results indicated that men had a higher probability of endorsing substance use compared with women. The index significantly predicted health, psychiatric, and psychosocial disturbances as well as level of substance use behavior and severity of SUD after a 2-year follow-up. Finally, this index is a reliable and useful prognostic indicator of the risk for SUD and the medical and psychosocial sequelae of drug consumption., (C) 2002 by the American Psychological AssociationComparability, validity, and impact of loss of information of a computerized adaptive administration of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) were assessed in a sample of 140 Veterans Affairs hospital patients. The countdown method ( Butcher, Keller, & Bacon, 1985) was used to adaptively administer Scales L (Lie) and F (Frequency), the 10 clinical scales, and the 15 content scales. Participants completed the MMPI-2 twice, in 1 of 2 conditions: computerized conventional test-retest, or computerized conventional-computerized adaptive. Mean profiles and test-retest correlations across modalities were comparable. Correlations between MMPI-2 scales and criterion measures supported the validity of the countdown method, although some attenuation of validity was suggested for certain health-related items. Loss of information incurred with this mode of adaptive testing has minimal impact on test validity. Item and time savings were substantial., (C) 1999 by the American Psychological Association10aPsychometrics10aSubstance-Related Disorders1 aKahler, C W1 aStrong, D R1 aRead, J P1 aDe Boeck, P1 aWilson, M1 aActon, G S1 aPalfai, T P1 aWood, M D1 aMehta, P D1 aNeale, M C1 aFlay, B R1 aConklin, C A1 aClayton, R R1 aTiffany, S T1 aShiffman, S1 aKrueger, R F1 aNichol, P E1 aHicks, B M1 aMarkon, K E1 aPatrick, C J1 aIacono, William, G1 aMcGue, Matt1 aLangenbucher, J W1 aLabouvie, E1 aMartin, C S1 aSanjuan, P M1 aBavly, L1 aKirisci, L1 aChung, T1 aVanyukov, M1 aDunn, M1 aTarter, R1 aHandel, R W1 aBen-Porath, Y S1 aWatt, M uhttp://mail.iacat.org/content/toward-efficient-and-comprehensive-measurement-alcohol-problems-continuum-college-students00503nas a2200109 4500008004100000245011600041210006900157260001700226100001400243700001300257856012300270 2004 eng d00aAchieving accuracy of retest calibration for a national CAT placement examination with a restricted test length0 aAchieving accuracy of retest calibration for a national CAT plac aSan Diego CA1 aWang, X B1 aWiley, A uhttp://mail.iacat.org/content/achieving-accuracy-retest-calibration-national-cat-placement-examination-restricted-test01669nas a2200229 4500008004100000245005500041210005300096300000800149490000700157520102900164653002101193653001201214653003001226653001801256653000901274100001701283700001201300700001501312700001601327700001401343856008201357 2004 eng d00aAssisted self-adapted testing: A comparative study0 aAssisted selfadapted testing A comparative study a2-90 v203 aA new type of self-adapted test (S-AT), called Assisted Self-Adapted Test (AS-AT), is presented. It differs from an ordinary S-AT in that prior to selecting the difficulty category, the computer advises examinees on their best difficulty category choice, based on their previous performance. Three tests (computerized adaptive test, AS-AT, and S-AT) were compared regarding both their psychometric (precision and efficiency) and psychological (anxiety) characteristics. Tests were applied in an actual assessment situation, in which test scores determined 20% of term grades. A sample of 173 high school students participated. Neither differences in posttest anxiety nor ability were obtained. Concerning precision, AS-AT was as precise as CAT, and both revealed more precision than S-AT. It was concluded that AS-AT acted as a CAT concerning precision. Some hints, but not conclusive support, of the psychological similarity between AS-AT and S-AT was also found. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAdaptive Testing10aAnxiety10aComputer Assisted Testing10aPsychometrics10aTest1 aHontangas, P1 aOlea, J1 aPonsoda, V1 aRevuelta, J1 aWise, S L uhttp://mail.iacat.org/content/assisted-self-adapted-testing-comparative-study00507nas a2200121 4500008004100000245009000041210006900131260001700200100001700217700001900234700001500253856011700268 2004 eng d00aCombining computer adaptive testing technology with cognitively diagnostic assessment0 aCombining computer adaptive testing technology with cognitively  aSan Diego CA1 aMcGlohen, MK1 aChang, Hua-Hua1 aWills, J T uhttp://mail.iacat.org/content/combining-computer-adaptive-testing-technology-cognitively-diagnostic-assessment-000512nas a2200133 4500008004100000245005100041210005100092260009900143100001700242700001600259700001400275700000800289856008100297 2004 eng d00aComputerized adaptive testing and item banking0 aComputerized adaptive testing and item banking aP. M. Fayers and R. D. Hays (Eds.) Assessing Quality of Life. Oxford: Oxford University Press.1 aBjorner, J B1 aKosinski, M1 aWare, J E1 aJr. uhttp://mail.iacat.org/content/computerized-adaptive-testing-and-item-banking00482nas a2200109 4500008004500000245010200045210006900147300001000216490000700226100001400233856012500247 2004 Engldsh 00aComputerized Adaptive Testing for Effective and Efficient Measurement in Counseling and Education0 aComputerized Adaptive Testing for Effective and Efficient Measur a70-840 v371 aWeiss, DJ uhttp://mail.iacat.org/content/computerized-adaptive-testing-effective-and-efficient-measurement-counseling-and-education00427nas a2200109 4500008004100000245006900041210006900110260002100179100001100200700001200211856009400223 2004 eng d00aEvaluating scale stability of a computer adaptive testing system0 aEvaluating scale stability of a computer adaptive testing system aMcLean, VAbGMAC1 aGuo, F1 aWang, L uhttp://mail.iacat.org/content/evaluating-scale-stability-computer-adaptive-testing-system01192nas a2200133 4500008003900000245009600039210006900135300001200204490000700216520074500223100002000968700001700988856005301005 2004 d00aImplementation and Measurement Efficiency of Multidimensional Computerized Adaptive Testing0 aImplementation and Measurement Efficiency of Multidimensional Co a295-3160 v283 a

Multidimensional adaptive testing (MAT) procedures are proposed for the measurement of several latent traits by a single examination. Bayesian latent trait estimation and adaptive item selection are derived. Simulations were conducted to compare the measurement efficiency of MAT with those of unidimensional adaptive testing and random administration. The results showed that the higher the correlation between latent traits, the more latent traits there were, and the more scoring levels there were in the items, the more efficient MAT was than the other two procedures. For tests containing multidimensional items, only MAT is applicable, whereas unidimensional adaptive testing is not. Issues in implementing MAT are discussed.

1 aWang, Wen-Chung1 aChen, Po-Hsi uhttp://apm.sagepub.com/content/28/5/295.abstract00710nas a2200157 4500008004100000245013900041210006900180260003200249653003400281653004000315653004100355100001200396700001200408700001200420856012000432 2004 eng d00aAn investigation of two combination procedures of SPRT for three-category classification decisions in computerized classification test0 ainvestigation of two combination procedures of SPRT for threecat aSan Antonio, Texasc04/200410acomputerized adaptive testing10aComputerized classification testing10asequential probability ratio testing1 aJiao, H1 aWang, S1 aLau, CA uhttp://mail.iacat.org/content/investigation-two-combination-procedures-sprt-three-category-classification-decisions00614nas a2200121 4500008004100000245012400041210006900165260010500234100001200339700001200351700001100363856011800374 2004 eng d00aAn investigation of two combination procedures of SPRT for three-category decisions in computerized classification test0 ainvestigation of two combination procedures of SPRT for threecat aPaper presented at the annual meeting of the American Educational Research Association, San Diego CA1 aJiao, H1 aWang, S1 aLau, A uhttp://mail.iacat.org/content/investigation-two-combination-procedures-sprt-three-category-decisions-computerized00424nas a2200097 4500008004100000245007800041210006900119260001700188100001600205856010500221 2004 eng d00aMutual information item selection in multiple-category classification CAT0 aMutual information item selection in multiplecategory classifica aSan Diego CA1 aWeissman, A uhttp://mail.iacat.org/content/mutual-information-item-selection-multiple-category-classification-cat00329nas a2200097 4500008004100000245004500041210004500086260001700131100001200148856007100160 2004 eng d00aNew methods for CBT item pool evaluation0 aNew methods for CBT item pool evaluation aSan Diego CA1 aWang, L uhttp://mail.iacat.org/content/new-methods-cbt-item-pool-evaluation00639nas a2200193 4500008004100000245009100041210006900132300000900201490000700210100001400217700001600231700001400247700001700261700002000278700001400298700001500312700001200327856010600339 2004 eng d00aValidating the German computerized adaptive test for anxiety on healthy sample (A-CAT)0 aValidating the German computerized adaptive test for anxiety on  a15150 v131 aBecker, J1 aWalter, O B1 aFliege, H1 aBjorner, J B1 aKocalevent, R D1 aSchmid, G1 aKlapp, B F1 aRose, M uhttp://mail.iacat.org/content/validating-german-computerized-adaptive-test-anxiety-healthy-sample-cat00419nas a2200097 4500008004100000245008000041210006900121260001500190100001600205856010000221 2003 eng d00aAssessing the efficiency of item selection in computerized adaptive testing0 aAssessing the efficiency of item selection in computerized adapt aChicago IL1 aWeissman, A uhttp://mail.iacat.org/content/assessing-efficiency-item-selection-computerized-adaptive-testing00509nas a2200109 4500008004100000245012000041210006900161260001500230100001500245700001600260856012300276 2003 eng d00aCalibrating CAT pools and online pretest items using nonparametric and adjusted marginal maximum likelihood methods0 aCalibrating CAT pools and online pretest items using nonparametr aChicago IL1 aKrass, I A1 aWilliams, B uhttp://mail.iacat.org/content/calibrating-cat-pools-and-online-pretest-items-using-nonparametric-and-adjusted-marginal02655nas a2200385 4500008004100000245014400041210006900185300001200254490000700266520138100273653002101654653003301675653002901708653001501737653001001752653000901762653002201771653002601793653003301819653002501852653001901877653001001896653002501906653001601931653002401947653002601971653002701997653003202024653001302056653002802069100001702097700001602114700001402130856012502144 2003 eng d00aCalibration of an item pool for assessing the burden of headaches: an application of item response theory to the Headache Impact Test (HIT)0 aCalibration of an item pool for assessing the burden of headache a913-9330 v123 aBACKGROUND: Measurement of headache impact is important in clinical trials, case detection, and the clinical monitoring of patients. Computerized adaptive testing (CAT) of headache impact has potential advantages over traditional fixed-length tests in terms of precision, relevance, real-time quality control and flexibility. OBJECTIVE: To develop an item pool that can be used for a computerized adaptive test of headache impact. METHODS: We analyzed responses to four well-known tests of headache impact from a population-based sample of recent headache sufferers (n = 1016). We used confirmatory factor analysis for categorical data and analyses based on item response theory (IRT). RESULTS: In factor analyses, we found very high correlations between the factors hypothesized by the original test constructers, both within and between the original questionnaires. These results suggest that a single score of headache impact is sufficient. We established a pool of 47 items which fitted the generalized partial credit IRT model. By simulating a computerized adaptive health test we showed that an adaptive test of only five items had a very high concordance with the score based on all items and that different worst-case item selection scenarios did not lead to bias. CONCLUSION: We have established a headache impact item pool that can be used in CAT of headache impact.10a*Cost of Illness10a*Decision Support Techniques10a*Sickness Impact Profile10aAdolescent10aAdult10aAged10aComparative Study10aDisability Evaluation10aFactor Analysis, Statistical10aHeadache/*psychology10aHealth Surveys10aHuman10aLongitudinal Studies10aMiddle Aged10aMigraine/psychology10aModels, Psychological10aPsychometrics/*methods10aQuality of Life/*psychology10aSoftware10aSupport, Non-U.S. Gov't1 aBjorner, J B1 aKosinski, M1 aWare, Jr. uhttp://mail.iacat.org/content/calibration-item-pool-assessing-burden-headaches-application-item-response-theory-headache00510nas a2200133 4500008004100000245008300041210006900124260001500193100001500208700001900223700001300242700001200255856010900267 2003 eng d00aComputerized adaptive testing: A comparison of three content balancing methods0 aComputerized adaptive testing A comparison of three content bala aChicago IL1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T1 aWen, z. uhttp://mail.iacat.org/content/computerized-adaptive-testing-comparison-three-content-balancing-methods-000469nas a2200133 4500008004100000245006800041210006800109260001500177100001000192700001600202700001200218700001300230856009200243 2003 eng d00aEffects of test administration mode on item parameter estimates0 aEffects of test administration mode on item parameter estimates aChicago IL1 aYi, Q1 aHarris, D J1 aWang, T1 aBan, J-C uhttp://mail.iacat.org/content/effects-test-administration-mode-item-parameter-estimates00546nas a2200145 4500008004100000245009500041210006900136260001500205100001000220700001600230700001400246700001300260700001500273856011200288 2003 eng d00aEvaluating computerized adaptive testing design for the MCAT with realistic simulated data0 aEvaluating computerized adaptive testing design for the MCAT wit aChicago IL1 aLu, Y1 aPitoniak, M1 aRizavi, S1 aWay, W D1 aSteffan, M uhttp://mail.iacat.org/content/evaluating-computerized-adaptive-testing-design-mcat-realistic-simulated-data03167nas a2200361 4500008004100000245012500041210006900166300001200235490000700247520200400254653002902258653001502287653001002302653000902312653002202321653002002343653003302363653002402396653001102420653001002431653000902441653001602450653002502466653002602491653004302517653003202560653001902592653002802611100001702639700001602656700001402672856011902686 2003 eng d00aThe feasibility of applying item response theory to measures of migraine impact: a re-analysis of three clinical studies0 afeasibility of applying item response theory to measures of migr a887-9020 v123 aBACKGROUND: Item response theory (IRT) is a powerful framework for analyzing multiitem scales and is central to the implementation of computerized adaptive testing. OBJECTIVES: To explain the use of IRT to examine measurement properties and to apply IRT to a questionnaire for measuring migraine impact--the Migraine Specific Questionnaire (MSQ). METHODS: Data from three clinical studies that employed the MSQ-version 1 were analyzed by confirmatory factor analysis for categorical data and by IRT modeling. RESULTS: Confirmatory factor analyses showed very high correlations between the factors hypothesized by the original test constructions. Further, high item loadings on one common factor suggest that migraine impact may be adequately assessed by only one score. IRT analyses of the MSQ were feasible and provided several suggestions as to how to improve the items and in particular the response choices. Out of 15 items, 13 showed adequate fit to the IRT model. In general, IRT scores were strongly associated with the scores proposed by the original test developers and with the total item sum score. Analysis of response consistency showed that more than 90% of the patients answered consistently according to a unidimensional IRT model. For the remaining patients, scores on the dimension of emotional function were less strongly related to the overall IRT scores that mainly reflected role limitations. Such response patterns can be detected easily using response consistency indices. Analysis of test precision across score levels revealed that the MSQ was most precise at one standard deviation worse than the mean impact level for migraine patients that are not in treatment. Thus, gains in test precision can be achieved by developing items aimed at less severe levels of migraine impact. CONCLUSIONS: IRT proved useful for analyzing the MSQ. The approach warrants further testing in a more comprehensive item pool for headache impact that would enable computerized adaptive testing.10a*Sickness Impact Profile10aAdolescent10aAdult10aAged10aComparative Study10aCost of Illness10aFactor Analysis, Statistical10aFeasibility Studies10aFemale10aHuman10aMale10aMiddle Aged10aMigraine/*psychology10aModels, Psychological10aPsychometrics/instrumentation/*methods10aQuality of Life/*psychology10aQuestionnaires10aSupport, Non-U.S. Gov't1 aBjorner, J B1 aKosinski, M1 aWare, Jr. uhttp://mail.iacat.org/content/feasibility-applying-item-response-theory-measures-migraine-impact-re-analysis-three00521nas a2200157 4500008004100000245007400041210006900115490000700184100001500191700001200206700001100218700001100229700001800240700001600258856008900274 2003 eng d00aA feasibility study of on-the-fly item generation in adaptive testing0 afeasibility study of onthefly item generation in adaptive testin0 v2 1 aBejar, I I1 aLawless1 aMorley1 aWagner1 aBennett R. E.1 aRevuelta, J uhttp://mail.iacat.org/content/feasibility-study-fly-item-generation-adaptive-testing00539nas a2200121 4500008004100000245013200041210006900173260001500242100001000257700001200267700001200279856012600291 2003 eng d00aImplementing the a-stratified method with b blocking in computerized adaptive testing with the generalized partial credit model0 aImplementing the astratified method with b blocking in computeri aChicago IL1 aYi, Q1 aWang, T1 aWang, S uhttp://mail.iacat.org/content/implementing-stratified-method-b-blocking-computerized-adaptive-testing-generalized-partial00367nas a2200097 4500008004100000245005500041210005500096260002000151100001600171856008200187 2003 eng d00aInformation theoretic approaches to item selection0 aInformation theoretic approaches to item selection aSardinia, Italy1 aWeissman, A uhttp://mail.iacat.org/content/information-theoretic-approaches-item-selection00394nas a2200109 4500008004100000245006000041210006000101260001500161100001100176700001200187856008500199 2003 eng d00aOnline calibration and scale stability of a CAT program0 aOnline calibration and scale stability of a CAT program aChicago IL1 aGuo, F1 aWang, G uhttp://mail.iacat.org/content/online-calibration-and-scale-stability-cat-program00428nas a2200109 4500008004100000245007600041210006900117300001100186490000700197100001400204856010000218 2003 eng d00aAn optimal design approach to criterion-referenced computerized testing0 aoptimal design approach to criterionreferenced computerized test a97-1000 v281 aWiberg, M uhttp://mail.iacat.org/content/optimal-design-approach-criterion-referenced-computerized-testing02860nas a2200265 4500008004100000245006600041210006600107260000800173300000900181490000700190520208800197653002102285653002902306653003002335653001202365653001102377653001302388653003102401653001902432100001302451700001502464700001302479700001502492856008702507 2002 eng d00aAdvances in quality of life measurements in oncology patients0 aAdvances in quality of life measurements in oncology patients cJun a60-80 v293 aAccurate assessment of the quality of life (QOL) of patients can provide important clinical information to physicians, especially in the area of oncology. Changes in QOL are important indicators of the impact of a new cytotoxic therapy, can affect a patient's willingness to continue treatment, and may aid in defining response in the absence of quantifiable endpoints such as tumor regression. Because QOL is becoming an increasingly important aspect in the management of patients with malignant disease, it is vital that the instruments used to measure QOL are reliable and accurate. Assessment of QOL involves a multidimensional approach that includes physical, functional, social, and emotional well-being, and the most comprehensive instruments measure at least three of these domains. Instruments to measure QOL can be generic (eg, the Nottingham Health Profile), targeted toward specific illnesses (eg, Functional Assessment of Cancer Therapy - Lung), or be a combination of generic and targeted. Two of the most widely used examples of the combination, or hybrid, instruments are the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 Items and the Functional Assessment of Chronic Illness Therapy. A consequence of the increasing international collaboration in clinical trials has been the growing necessity for instruments that are valid across languages and cultures. To assure the continuing reliability and validity of QOL instruments in this regard, item response theory can be applied. Techniques such as item response theory may be used in the future to construct QOL item banks containing large sets of validated questions that represent various levels of QOL domains. As QOL becomes increasingly important in understanding and approaching the overall management of cancer patients, the tools available to clinicians and researchers to assess QOL will continue to evolve. While the instruments currently available provide reliable and valid measurement, further improvements in precision and application are anticipated.10a*Quality of Life10a*Sickness Impact Profile10aCross-Cultural Comparison10aCulture10aHumans10aLanguage10aNeoplasms/*physiopathology10aQuestionnaires1 aCella, D1 aChang, C-H1 aLai, J S1 aWebster, K uhttp://mail.iacat.org/content/advances-quality-life-measurements-oncology-patients00471nam a2200097 4500008004100000245008000041210006900121260006500190100001600255856010200271 2002 eng d00aAssessing the efficiency of item selection in computerized adaptive testing0 aAssessing the efficiency of item selection in computerized adapt aUnpublished doctoral dissertation, University of Pittsburgh.1 aWeissman, A uhttp://mail.iacat.org/content/assessing-efficiency-item-selection-computerized-adaptive-testing-002895nas a2200349 4500008004100000245008300041210006900124260000800193300001100201490000700212520176600219653003001985653002802015653001502043653001002058653000902068653002202077653001102099653001902110653001102129653000902140653001602149653006202165653006102227653003302288653003602321653003102357653002602388100001402414700001602428856010102444 2002 eng d00aDevelopment of an index of physical functional health status in rehabilitation0 aDevelopment of an index of physical functional health status in  cMay a655-650 v833 aOBJECTIVE: To describe (1) the development of an index of physical functional health status (FHS) and (2) its hierarchical structure, unidimensionality, reproducibility of item calibrations, and practical application. DESIGN: Rasch analysis of existing data sets. SETTING: A total of 715 acute, orthopedic outpatient centers and 62 long-term care facilities in 41 states participating with Focus On Therapeutic Outcomes, Inc. PATIENTS: A convenience sample of 92,343 patients (40% male; mean age +/- standard deviation [SD], 48+/-17y; range, 14-99y) seeking rehabilitation between 1993 and 1999. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Patients completed self-report health status surveys at admission and discharge. The Medical Outcomes Study 36-Item Short-Form Health Survey's physical functioning scale (PF-10) is the foundation of the physical FHS. The Oswestry Low Back Pain Disability Questionnaire, Neck Disability Index, Lysholm Knee Questionnaire, items pertinent to patients with upper-extremity impairments, and items pertinent to patients with more involved neuromusculoskeletal impairments were cocalibrated into the PF-10. RESULTS: The final FHS item bank contained 36 items (patient separation, 2.3; root mean square measurement error, 5.9; mean square +/- SD infit, 0.9+/-0.5; outfit, 0.9+/-0.9). Analyses supported empirical item hierarchy, unidimensionality, reproducibility of item calibrations, and content and construct validity of the FHS-36. CONCLUSIONS: Results support the reliability and validity of FHS-36 measures in the present sample. Analyses show the potential for a dynamic, computer-controlled, adaptive survey for FHS assessment applicable for group analysis and clinical decision making for individual patients.10a*Health Status Indicators10a*Rehabilitation Centers10aAdolescent10aAdult10aAged10aAged, 80 and over10aFemale10aHealth Surveys10aHumans10aMale10aMiddle Aged10aMusculoskeletal Diseases/*physiopathology/*rehabilitation10aNervous System Diseases/*physiopathology/*rehabilitation10aPhysical Fitness/*physiology10aRecovery of Function/physiology10aReproducibility of Results10aRetrospective Studies1 aHart, D L1 aWright, B D uhttp://mail.iacat.org/content/development-index-physical-functional-health-status-rehabilitation00695nas a2200157 4500008003900000245010200039210006900141260011300210100001500323700001700338700001600355700001600371700001700387700001600404856011700420 2002 d00aA feasibility study of on-the-fly item generation in adaptive testing (GRE Board Report No 98-12)0 afeasibility study of onthefly item generation in adaptive testin aEducational Testing Service RR02-23. Princeton NJ: Educational Testing Service. Note = “{PDF file, 193 KB}1 aBejar, I I1 aLawless, R R1 aMorley, M E1 aWagner, M E1 aBennett, R E1 aRevuelta, J uhttp://mail.iacat.org/content/feasibility-study-fly-item-generation-adaptive-testing-gre-board-report-no-98-12-000461nas a2200121 4500008004100000245007300041210006900114260001900183100001400202700001900216700001300235856009100248 2002 eng d00aOptimum number of strata in the a-stratified adaptive testing design0 aOptimum number of strata in the astratified adaptive testing des aNew Orleans LA1 aWen, J -B1 aChang, Hua-Hua1 aHau, K-T uhttp://mail.iacat.org/content/optimum-number-strata-stratified-adaptive-testing-design00533nas a2200109 4500008004100000245014600041210006900187260001900256100001200275700001200287856012400299 2002 eng d00aRelative precision of ability estimation in polytomous CAT: A comparison under the generalized partial credit model and graded response model0 aRelative precision of ability estimation in polytomous CAT A com aNew Orleans LA1 aWang, S1 aWang, T uhttp://mail.iacat.org/content/relative-precision-ability-estimation-polytomous-cat-comparison-under-generalized-partial00373nas a2200133 4500008004100000245003800041210003600079300001200115490000700127100001400134700001500148700001200163856006400175 2002 eng d00aSelf-adapted testing: An overview0 aSelfadapted testing An overview a107-1220 v121 aWise, S L1 aPonsoda, V1 aOlea, J uhttp://mail.iacat.org/content/self-adapted-testing-overview00510nas a2200109 4500008004100000245011100041210006900152260001900221100002000240700001500260856012500275 2002 eng d00aUsing testlet response theory to evaluate the equivalence of automatically generated multiple-choice items0 aUsing testlet response theory to evaluate the equivalence of aut aNew Orleans LA1 aWilliamson, D M1 aBejar, I I uhttp://mail.iacat.org/content/using-testlet-response-theory-evaluate-equivalence-automatically-generated-multiple-choice01150nas a2200205 4500008004100000245008200041210006900123260005600192520043100248653002100679653003000700653001600730653001600746653001800762100001500780700001700795700001700812700001400829856010100843 2002 eng d00aThe work ahead: A psychometric infrastructure for computerized adaptive tests0 awork ahead A psychometric infrastructure for computerized adapti aMahwah, N.J. USAbLawrence Erlbaum Associates, Inc.3 a(From the chapter) Considers the past and future of computerized adaptive tests and computer-based tests and looks at issues and challenges confronting a testing program as it implements and operates a computer-based test. Recommendations for testing programs from The National Council of Measurement in Education Ad Hoc Committee on Computerized Adaptive Test Disclosure are appended. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Assisted Testing10aEducational10aMeasurement10aPsychometrics1 aDrasgow, F1 aPotenza, M P1 aFreemer, J J1 aWard, W C uhttp://mail.iacat.org/content/work-ahead-psychometric-infrastructure-computerized-adaptive-tests00493nas a2200121 4500008004100000245008700041210006900128260001500197100001400212700001900226700001700245856010900262 2001 eng d00aAdaptation of a-stratified method in variable length computerized adaptive testing0 aAdaptation of astratified method in variable length computerized aSeattle WA1 aWen, J -B1 aChang, Hua-Hua1 aHau, K -T   uhttp://mail.iacat.org/content/adaptation-stratified-method-variable-length-computerized-adaptive-testing01946nas a2200169 4500008004100000245011100041210007100152300001200223490000700235520133200242100001301574700001601587700001201603700001001615700001601625856013501641 2001 eng d00aA comparative study of on line pretest item—Calibration/scaling methods in computerized adaptive testing0 acomparative study of on line pretest item—Calibrationscaling met a191-2120 v383 aThe purpose of this study was to compare and evaluate five on-line pretest item-calibration/scaling methods in computerized adaptive testing (CAT): marginal maximum likelihood estimate with one EM cycle (OEM), marginal maximum likelihood estimate with multiple EM cycles (MEM), Stocking's Method A, Stocking's Method B, and BILOG/Prior. The five methods were evaluated in terms ofitem-parameter recovery, using three different sample sizes (300, 1000 and 3000). The MEM method appeared to be the best choice among these, because it produced the smallest parameter-estimation errors for all sample size conditions. MEM and OEM are mathematically similar, although the OEM method produced larger errors. MEM also was preferable to OEM, unless the amount of timeinvolved in iterative computation is a concern. Stocking's Method B also worked very well, but it required anchor items that either would increase test lengths or require larger sample sizes depending on test administration design. Until more appropriate ways of handling sparse data are devised, the BILOG/Prior method may not be a reasonable choice for small sample sizes. Stocking's Method A hadthe largest weighted total error, as well as a theoretical weakness (i.e., treating estimated ability as true ability); thus, there appeared to be little reason to use it1 aBan, J C1 aHanson, B A1 aWang, T1 aYi, Q1 aHarris, D J uhttp://mail.iacat.org/content/comparative-study-line-pretest-item%E2%80%94calibrationscaling-methods-computerized-adaptive-testing00493nas a2200133 4500008004100000245007900041210006900120260001500189100001000204700001400214700001600228700001600244856009900260 2001 eng d00aComparison of the SPRT and CMT procedures in computerized adaptive testing0 aComparison of the SPRT and CMT procedures in computerized adapti aSeattle WA1 aYi, Q1 aHanson, B1 aWidiatmo, H1 aHarris, D J uhttp://mail.iacat.org/content/comparison-sprt-and-cmt-procedures-computerized-adaptive-testing00553nas a2200157 4500008004100000245008100041210006900122300001200191490000700203100002000210700001600230700001600246700001700262700001400279856010200293 2001 eng d00aDevelopment of an adaptive multimedia program to collect patient health data0 aDevelopment of an adaptive multimedia program to collect patient a320-3240 v211 aSutherland, L A1 aCampbell, M1 aOrnstein, K1 aWildemuth, B1 aLobach, D uhttp://mail.iacat.org/content/development-adaptive-multimedia-program-collect-patient-health-data00519nas a2200133 4500008003900000245009600039210006900135300000900204490000700213100001600220700001800236700001800254856011300272 2001 d00aAn examination of conditioning variables used in computer adaptive testing for DIF analyses0 aexamination of conditioning variables used in computer adaptive  a3-160 v141 aWalker, C M1 aBeretvas, S N1 aAckerman, T A uhttp://mail.iacat.org/content/examination-conditioning-variables-used-computer-adaptive-testing-dif-analyses00442nas a2200133 4500008004100000245005900041210005900100260001500159100001000174700001600184700001300200700001600213856007900229 2001 eng d00aImpact of scoring options for not reached items in CAT0 aImpact of scoring options for not reached items in CAT aSeattle WA1 aYi, Q1 aWidiatmo, H1 aBan, J-C1 aHarris, D J uhttp://mail.iacat.org/content/impact-scoring-options-not-reached-items-cat00475nas a2200109 4500008004100000245008400041210006900125260004000194100001200234700001500246856010400261 2001 eng d00aThe influence of item characteristics and administration position on CAT Scores0 ainfluence of item characteristics and administration position on aHudson Valley, NY, October 26, 20011 aWang, L1 aGawlick, L uhttp://mail.iacat.org/content/influence-item-characteristics-and-administration-position-cat-scores00451nas a2200109 4500008004100000245007700041210006900118260002100187100001400208700001500222856010400237 2001 eng d00aMeasurement efficiency of multidimensional computerized adaptive testing0 aMeasurement efficiency of multidimensional computerized adaptive aSan Francisco CA1 aWang, W-C1 aChen, B -H uhttp://mail.iacat.org/content/measurement-efficiency-multidimensional-computerized-adaptive-testing00504nas a2200133 4500008004100000245007900041210006900120260002400189100001500213700001400228700001700242700001200259856009900271 2001 eng d00aMonitoring items for changes in performance in computerized adaptive tests0 aMonitoring items for changes in performance in computerized adap aSeattle, Washington1 aSmith, R L1 aWang, M M1 aWingersky, M1 aZhao, C uhttp://mail.iacat.org/content/monitoring-items-changes-performance-computerized-adaptive-tests02032nas a2200253 4500008004100000245007700041210006900118260001200187300001200199490000700211520125800218653003901476653002901515653001501544653001001559653001101569653001101580653000901591653003001600653001301630100001601643700002001659856009901679 2001 eng d00aNCLEX-RN performance: predicting success on the computerized examination0 aNCLEXRN performance predicting success on the computerized exami cJul-Aug a158-1650 v173 aSince the adoption of the Computerized Adaptive Testing (CAT) format of the National Certification Licensure Examination for Registered Nurses (NCLEX-RN), no studies have been reported in the literature on predictors of successful performance by baccalaureate nursing graduates on the licensure examination. In this study, a discriminant analysis was used to identify which of 21 variables can be significant predictors of success on the CAT NCLEX-RN. The convenience sample consisted of 289 individuals who graduated from a baccalaureate nursing program between 1995 and 1998. Seven significant predictor variables were identified. The total number of C+ or lower grades earned in nursing theory courses was the best predictor, followed by grades in several individual nursing courses. More than 93 per cent of graduates were correctly classified. Ninety-four per cent of NCLEX "passes" were correctly classified, as were 92 per cent of NCLEX failures. This degree of accuracy in classifying CAT NCLEX-RN failures represents a marked improvement over results reported in previous studies of licensure examinations, and suggests the discriminant function will be helpful in identifying future students in danger of failure. J Prof Nurs 17:158-165, 2001.10a*Education, Nursing, Baccalaureate10a*Educational Measurement10a*Licensure10aAdult10aFemale10aHumans10aMale10aPredictive Value of Tests10aSoftware1 aBeeman, P B1 aWaterhouse, J K uhttp://mail.iacat.org/content/nclex-rn-performance-predicting-success-computerized-examination00472nas a2200109 4500008004100000245010000041210006900141300001200210490000700222100001200229856012100241 2001 eng d00aA new computer algorithm for simultaneous test construction of two-stage and multistage testing0 anew computer algorithm for simultaneous test construction of two a180-1980 v261 aWu, I L uhttp://mail.iacat.org/content/new-computer-algorithm-simultaneous-test-construction-two-stage-and-multistage-testing01706nas a2200181 4500008004100000245007300041210006900114300001100183490000700194520110100201653002101302653003001323653002501353653001501378100001701393700001501410856009901425 2001 eng d00aOutlier measures and norming methods for computerized adaptive tests0 aOutlier measures and norming methods for computerized adaptive t a85-1040 v263 aNotes that the problem of identifying outliers has 2 important aspects: the choice of outlier measures and the method to assess the degree of outlyingness (norming) of those measures. Several classes of measures for identifying outliers in Computerized Adaptive Tests (CATs) are introduced. Some of these measures are constructed to take advantage of CATs' sequential choice of items; other measures are taken directly from paper and pencil (P&P) tests and are used for baseline comparisons. Assessing the degree of outlyingness of CAT responses, however, can not be applied directly from P&P tests because stopping rules associated with CATs yield examinee responses of varying lengths. Standard outlier measures are highly correlated with the varying lengths which makes comparison across examinees impossible. Therefore, 4 methods are presented and compared which map outlier statistics to a familiar probability scale (a p value). The methods are explored in the context of CAT data from a 1995 Nationally Administered Computerized Examination (NACE). (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Assisted Testing10aStatistical Analysis10aTest Norms1 aBradlow, E T1 aWeiss, R E uhttp://mail.iacat.org/content/outlier-measures-and-norming-methods-computerized-adaptive-tests00899nas a2200121 4500008004100000245007300041210006900114490001100183520045200194100001500646700001900661856009700680 2001 eng d00aPolytomous modeling of cognitive errors in computer adaptive testing0 aPolytomous modeling of cognitive errors in computer adaptive tes0 v2 (4).3 aUsed Monte Carlo simulation to compare the relative measurement efficiency of polytomous modeling and dichotomous modeling under different scoring schemes and termination criteria. Results suggest that polytomous computerized adaptive testing (CAT) yields marginal gains over dichotomous CAT when termination criteria are more stringent. Discusses conditions under which polytomous CAT cannot prevent the nonuniform gain in test information. (SLD)1 aWang, L -S1 aLi., Chun-Shan uhttp://mail.iacat.org/content/polytomous-modeling-cognitive-errors-computer-adaptive-testing00489nas a2200121 4500008004100000245009800041210006900139300001200208490000700220100000900227700001200236856011900248 2001 eng d00aPrecision of Warm’s weighted likelihood estimation of ability for a polytomous model in CAT0 aPrecision of Warm s weighted likelihood estimation of ability fo a317-3310 v251 aWang1 aWang, T uhttp://mail.iacat.org/content/precision-warm%E2%80%99s-weighted-likelihood-estimation-ability-polytomous-model-cat00561nas a2200133 4500008004100000245009400041210006900135260004600204100001300250700001500263700001500278700001800293856011600311 2001 eng d00aRefining a system for computerized adaptive testing pool creation (Research Report 01-18)0 aRefining a system for computerized adaptive testing pool creatio aPrinceton NJ: Educational Testing Service1 aWay, W D1 aSwanson, L1 aSteffen, M1 aStocking, M L uhttp://mail.iacat.org/content/refining-system-computerized-adaptive-testing-pool-creation-research-report-01-1800452nas a2200121 4500008004100000245007000041210006900111260001500180100001300195700001200208700001600220856009400236 2001 eng d00aRefining a system for computerized adaptive testing pool creation0 aRefining a system for computerized adaptive testing pool creatio aSeattle WA1 aWay, W D1 aSwanson1 aStocking, M uhttp://mail.iacat.org/content/refining-system-computerized-adaptive-testing-pool-creation00532nas a2200121 4500008004100000245009200041210006900133260004600202100001300248700001700261700001600278856011600294 2001 eng d00aScoring alternatives for incomplete computerized adaptive tests (Research Report 01-20)0 aScoring alternatives for incomplete computerized adaptive tests  aPrinceton NJ: Educational Testing Service1 aWay, W D1 aGawlick, L A1 aEignor, D R uhttp://mail.iacat.org/content/scoring-alternatives-incomplete-computerized-adaptive-tests-research-report-01-2000318nas a2200097 4500008004100000245004500041210004100086260001500127100001600142856006200158 2001 eng d00aA system for on-the-fly adaptive testing0 asystem for onthefly adaptive testing aSeattle WA1 aWagner, M E uhttp://mail.iacat.org/content/system-fly-adaptive-testing00723nas a2200145 4500008004100000245020100041210006900242260005700311100001700368700001700385700001400402700002000416700001600436856012500452 2001 eng d00aTesting via the Internet: A literature review and analysis of issues for Department of Defense Internet testing of the Armed Services Vocational Aptitude Battery (ASVAB) in high schools (FR-01-12)0 aTesting via the Internet A literature review and analysis of iss aAlexandria VA: Human Resources Research Organization1 aMcBride, J R1 aPaddock, A F1 aWise, L L1 aStrickland, W J1 aWaters, B K uhttp://mail.iacat.org/content/testing-internet-literature-review-and-analysis-issues-department-defense-internet-testing00568nas a2200121 4500008004100000245012200041210006900163260004700232100001200279700001700291700001100308856012700319 2001 eng d00aUser's guide for SCORIGHT (version 1): A computer program for scoring tests built of testlets (Research Report 01-06)0 aUsers guide for SCORIGHT version 1 A computer program for scorin aPrinceton NJ: Educational Testing Service.1 aWang, X1 aBradlow, E T1 aWainer uhttp://mail.iacat.org/content/users-guide-scoright-version-1-computer-program-scoring-tests-built-testlets-research-report00568nas a2200121 4500008004100000245012200041210006900163260004700232100001200279700001700291700001100308856012700319 2001 eng d00aUsers guide for SCORIGHT (version 2) : A computer program for scoring tests built of testlets (Research Report 01-06)0 aUsers guide for SCORIGHT version 2 A computer program for scorin aPrinceton NJ: Educational Testing Service.1 aWang, X1 aBradlow, E T1 aWainer uhttp://mail.iacat.org/content/users-guide-scoright-version-2-computer-program-scoring-tests-built-testlets-research-report00471nas a2200133 4500008004100000245006900041210006900110260001600179100001200195700001100207700001300218700001100231856009500242 2000 eng d00aAssembling parallel item pools for computerized adaptive testing0 aAssembling parallel item pools for computerized adaptive testing aNew Orleans1 aWang, T1 aFan, Q1 aBan, J C1 aZhu, D uhttp://mail.iacat.org/content/assembling-parallel-item-pools-computerized-adaptive-testing00598nas a2200109 4500008004100000245010000041210006900141260012600210100001100336700001600347856012500363 2000 eng d00aCaveats, pitfalls, and unexpected consequences of implementing large-scale computerized testing0 aCaveats pitfalls and unexpected consequences of implementing lar aWainer, H. (Ed). Computerized adaptive testing: A primer (2nd ed.). pp. 271-299. Mahwah, NJ: Lawrence Erlbaum Associates.1 aWainer1 aEignor, D R uhttp://mail.iacat.org/content/caveats-pitfalls-and-unexpected-consequences-implementing-large-scale-computerized-testing00451nas a2200145 4500008004100000245005800041210005400099300000900153490000700162100001700169700001500186700001200201700001400213856007800227 2000 eng d00aThe choice of item difficulty in self adapted testing0 achoice of item difficulty in self adapted testing a3-120 v161 aHontangas, P1 aPonsoda, V1 aOlea, J1 aWise, S L uhttp://mail.iacat.org/content/choice-item-difficulty-self-adapted-testing00588nam a2200181 4500008004100000245005800041210005500099260005100154100001100205700001400216700001600230700001600246700001400262700001500276700001700291700001500308856008300323 2000 eng d00aComputerized adaptive testing: A primer (2nd edition)0 aComputerized adaptive testing A primer 2nd edition aHillsdale, N. J. : Lawrence Erlbaum Associates1 aWainer1 aDorans, N1 aEignor, D R1 aFlaugher, R1 aGreen, BF1 aMislevy, R1 aSteinberg, L1 aThissen, D uhttp://mail.iacat.org/content/computerized-adaptive-testing-primer-2nd-edition00476nas a2200133 4500008004100000245007200041210006900113260001900182100001300201700001200214700001000226700001600236856009000252 2000 eng d00aEffects of nonequivalence of item pools on ability estimates in CAT0 aEffects of nonequivalence of item pools on ability estimates in  aNew Orleans LA1 aBan, J C1 aWang, T1 aYi, Q1 aHarris, D J uhttp://mail.iacat.org/content/effects-nonequivalence-item-pools-ability-estimates-cat00499nas a2200133 4500008004100000245006100041210006000102260005900162300001200221100001600233700001100249700001700260856008800277 2000 eng d00aMML and EAP estimation in testlet-based adaptive testing0 aMML and EAP estimation in testletbased adaptive testing aDordrecht, The NetherlandsbKluwer Academic Publishers a271-2871 aGlas, C A W1 aWainer1 aBradlow, E T uhttp://mail.iacat.org/content/mml-and-eap-estimation-testlet-based-adaptive-testing00468nas a2200109 4500008004100000245009400041210006900135260001600204100001100220700001200231856011500243 2000 eng d00aA new item selection procedure for mixed item type in computerized classification testing0 anew item selection procedure for mixed item type in computerized aNew Orleans1 aLau, C1 aWang, T uhttp://mail.iacat.org/content/new-item-selection-procedure-mixed-item-type-computerized-classification-testing00489nas a2200121 4500008003900000245009100039210006900130300001200199490000700211100001400218700001900232856011600251 2000 d00aPractical issues in developing and maintaining a computerized adaptive testing program0 aPractical issues in developing and maintaining a computerized ad a135-1550 v211 aWise, S L1 aKingsbury, G G uhttp://mail.iacat.org/content/practical-issues-developing-and-maintaining-computerized-adaptive-testing-program00389nas a2200109 4500008004100000245005900041210005700100300001200157490000700169100001100176856009200187 2000 eng d00aRescuing computerized testing by breaking Zipf’s law0 aRescuing computerized testing by breaking Zipf s law a203-2240 v251 aWainer uhttp://mail.iacat.org/content/rescuing-computerized-testing-breaking-zipf%E2%80%99s-law00639nas a2200133 4500008004100000245020600041210006900247300001000316490000700326100001400333700001700347700001600364856012500380 2000 eng d00aResponse to Hays et al and McHorney and Cohen: Practical implications of item response theory and computerized adaptive testing: A brief summary of ongoing studies of widely used headache impact scales0 aResponse to Hays et al and McHorney and Cohen Practical implicat a73-820 v381 aWare, Jr.1 aBjorner, J B1 aKosinski, M uhttp://mail.iacat.org/content/response-hays-et-al-and-mchorney-and-cohen-practical-implications-item-response-theory-and00422nas a2200121 4500008004100000245006000041210006000101260001600161100001100177700001300188700001600201856008300217 2000 eng d00aTest security and the development of computerized tests0 aTest security and the development of computerized tests aNew Orleans1 aGuo, F1 aWay, W D1 aReshetar, R uhttp://mail.iacat.org/content/test-security-and-development-computerized-tests00618nas a2200121 4500008004100000245009800041210006900139260013700208100001100345700001700356700001000373856011300383 2000 eng d00aTestlet response theory: An analog for the 3PL model useful in testlet-based adaptive testing0 aTestlet response theory An analog for the 3PL model useful in te aW. J. van der Linden and C. A. W. Glas (Eds.), Computerized Adaptive Testing: Theory and Practice (pp. 245-270). Norwell MA: Kluwer.1 aWainer1 aBradlow, E T1 aDu, Z uhttp://mail.iacat.org/content/testlet-response-theory-analog-3pl-model-useful-testlet-based-adaptive-testing00507nas a2200145 4500008004100000245007100041210006900112260002100181100001200202700001000214700001300224700001600237700001600253856009200269 1999 eng d00aAdjusting "scores" from a CAT following successful item challenges0 aAdjusting scores from a CAT following successful item challenges aMontreal, Canada1 aWang, T1 aYi, Q1 aBan, J C1 aHarris, D J1 aHanson, B A uhttp://mail.iacat.org/content/adjusting-scores-cat-following-successful-item-challenges00405nas a2200133 4500008004100000245005000041210004700091300001200138490000800150100001700158700001100175700001200186856007300198 1999 eng d00aA Bayesian random effects model for testlets 0 aBayesian random effects model for testlets a153-1680 v 641 aBradlow, E T1 aWainer1 aWang, X uhttp://mail.iacat.org/content/bayesian-random-effects-model-testlets00576nas a2200145 4500008004100000245011800041210006900159300001200228490000700240100001700247700001700264700001200281700001500293856012200308 1999 eng d00aCan examinees use a review option to obtain positively biased ability estimates on a computerized adaptive test? 0 aCan examinees use a review option to obtain positively biased ab a141-1570 v361 aVispoel, W P1 aRocklin, T R1 aWang, T1 aBleiler, T uhttp://mail.iacat.org/content/can-examinees-use-review-option-obtain-positively-biased-ability-estimates-computerized00393nas a2200097 4500008004100000245006400041210006400105260002100169100001400190856009100204 1999 eng d00aComparison of stratum scored and maximum likelihood scoring0 aComparison of stratum scored and maximum likelihood scoring aMontreal, Canada1 aWise, S L uhttp://mail.iacat.org/content/comparison-stratum-scored-and-maximum-likelihood-scoring00526nas a2200121 4500008004100000245012600041210006900167260001600236100001100252700001200263700001000275856011900285 1999 eng d00aComparison of the a-stratified method, the Sympson-Hetter method, and the matched difficulty method in CAT administration0 aComparison of the astratified method the SympsonHetter method an aLawrence KS1 aBan, J1 aWang, T1 aYi, Q uhttp://mail.iacat.org/content/comparison-stratified-method-sympson-hetter-method-and-matched-difficulty-method-cat00479nas a2200133 4500008004100000245007500041210006900116300001200185490000700197100001600204700002000220700001400240856009100254 1999 eng d00aComputerized adaptive assessment with the MMPI-2 in a clinical setting0 aComputerized adaptive assessment with the MMPI2 in a clinical se a369-3800 v111 aHandel, R W1 aBen-Porath, Y S1 aWatt, M E uhttp://mail.iacat.org/content/computerized-adaptive-assessment-mmpi-2-clinical-setting00462nas a2200109 4500008004100000245009200041210006900133260001300202100000800215700001200223856011700235 1999 eng d00aComputerized classification testing under practical constraints with a polytomous model0 aComputerized classification testing under practical constraints  aMontreal1 aLau1 aWang, T uhttp://mail.iacat.org/content/computerized-classification-testing-under-practical-constraints-polytomous-model-000489nas a2200109 4500008004100000245009200041210006900133260003800202100001200240700001200252856011500264 1999 eng d00aComputerized classification testing under practical constraints with a polytomous model0 aComputerized classification testing under practical constraints  aMontreal, Quebec, Canadac04/19991 aLau, CA1 aWang, T uhttp://mail.iacat.org/content/computerized-classification-testing-under-practical-constraints-polytomous-model00487nas a2200097 4500008004100000245011700041210006900158260002100227100002000248856012100268 1999 eng d00aThe development and cognitive evaluation of an audio-assisted computer-adaptive test for eight-grade mathematics0 adevelopment and cognitive evaluation of an audioassisted compute aMontreal, Canada1 aWilliams, V S L uhttp://mail.iacat.org/content/development-and-cognitive-evaluation-audio-assisted-computer-adaptive-test-eight-grade00504nas a2200121 4500008004100000245009700041210006900138300001000207100001400217700001700231700001600248856011800264 1999 eng d00aDynamic health assessments: The search for more practical and more precise outcomes measures0 aDynamic health assessments The search for more practical and mor a11-131 aWare, Jr.1 aBjorner, J B1 aKosinski, M uhttp://mail.iacat.org/content/dynamic-health-assessments-search-more-practical-and-more-precise-outcomes-measures00499nas a2200109 4500008004100000245010400041210006900145260002100214100001600235700001800251856012000269 1999 eng d00aAn examination of conditioning variables in DIF analysis in a computer adaptive testing environment0 aexamination of conditioning variables in DIF analysis in a compu aMontreal, Canada1 aWalker, C M1 aAckerman, T A uhttp://mail.iacat.org/content/examination-conditioning-variables-dif-analysis-computer-adaptive-testing-environment00604nas a2200157 4500008004100000245011600041210006900157300001200226490000700238100001400245700001100259700001600270700001700286700001900303856012400322 1999 eng d00aExaminee judgments of changes in item difficulty: Implications for item review in computerized adaptive testing0 aExaminee judgments of changes in item difficulty Implications fo a185-1980 v121 aWise, S L1 aFinney1 aEnders, C K1 aFreeman, S A1 aSeverance, D D uhttp://mail.iacat.org/content/examinee-judgments-changes-item-difficulty-implications-item-review-computerized-adaptive00628nas a2200157 4500008004100000245011800041210006900159260002100228100001700249700001900266700001500285700001600300700001500316700001300331856012600344 1999 eng d00aLimiting answer review and change on computerized adaptive vocabulary tests: Psychometric and attitudinal results0 aLimiting answer review and change on computerized adaptive vocab aMontreal, Canada1 aVispoel, W P1 aHendrickson, A1 aBleiler, T1 aWidiatmo, H1 aShrairi, S1 aIhrig, D uhttp://mail.iacat.org/content/limiting-answer-review-and-change-computerized-adaptive-vocabulary-tests-psychometric-and-000536nam a2200097 4500008004100000245012500041210006900166260006400235100001200299856012700311 1999 eng d00aThe precision of ability estimation methods for computerized adaptive testing using the generalized partial credit model0 aprecision of ability estimation methods for computerized adaptiv aUnpublished doctoral dissertation, University of Pittsburgh1 aWang, S uhttp://mail.iacat.org/content/precision-ability-estimation-methods-computerized-adaptive-testing-using-generalized-partial00463nas a2200109 4500008004100000245009600041210006900137260001300206100001200219700001200231856011000243 1999 eng d00aPrecision of Warm's weighted likelihood estimation of ability for a polytomous model in CAT0 aPrecision of Warms weighted likelihood estimation of ability for aMontreal1 aWang, S1 aWang, T uhttp://mail.iacat.org/content/precision-warms-weighted-likelihood-estimation-ability-polytomous-model-cat00349nas a2200097 4500008004100000245005200041210004800093260002100141100001400162856007500176 1999 eng d00aThe rationale and principles of stratum scoring0 arationale and principles of stratum scoring aMontreal, Canada1 aWise, S L uhttp://mail.iacat.org/content/rationale-and-principles-stratum-scoring00468nas a2200133 4500008004100000245007000041210006900111300001200180490000700192100001200199700001600211700001600227856009100243 1999 eng d00aReducing bias in CAT trait estimation: A comparison of approaches0 aReducing bias in CAT trait estimation A comparison of approaches a263-2780 v231 aWang, T1 aHanson, B H1 aLau, C -M H uhttp://mail.iacat.org/content/reducing-bias-cat-trait-estimation-comparison-approaches00355nas a2200085 4500008004100000245006300041210006300104100001200167856009000179 1999 eng d00aSome relationship among issues in CAT item pool management0 aSome relationship among issues in CAT item pool management1 aWang, T uhttp://mail.iacat.org/content/some-relationship-among-issues-cat-item-pool-management00406nas a2200109 4500008004100000245006000041210005900101260002100160100001500181700001300196856008700209 1999 eng d00aTest-taking strategies in computerized adaptive testing0 aTesttaking strategies in computerized adaptive testing aMontreal, Canada1 aSteffen, M1 aWay, W D uhttp://mail.iacat.org/content/test-taking-strategies-computerized-adaptive-testing00494nas a2200133 4500008004100000245005700041210005700098260005700155100001400212700002100226700001600247700001400263856008300277 1998 eng d00aAlternatives for scoring computerized adaptive tests0 aAlternatives for scoring computerized adaptive tests aMahwah, N.J., USAbLawrence Erlbaum Associates, Inc.1 aDodd, B G1 aFitzpatrick, S J1 aFremer, J J1 aWard, W C uhttp://mail.iacat.org/content/alternatives-scoring-computerized-adaptive-tests01292nas a2200145 4500008004100000245007300041210006900114300001200183490000700195520080400202100001701006700001501023700001101038856009701049 1998 eng d00aBayesian identification of outliers in computerized adaptive testing0 aBayesian identification of outliers in computerized adaptive tes a910-9190 v933 aWe consider the problem of identifying examinees with aberrant response patterns in a computerized adaptive test (CAT). The vec-tor of responses yi of person i from the CAT comprise a multivariate response vector. Multivariate observations may be outlying in manydi erent directions and we characterize speci c directions as corre- sponding to outliers with different interpretations. We develop a class of outlier statistics to identify different types of outliers based on a con-trol chart type methodology. The outlier methodology is adaptable to general longitudinal discrete data structures. We consider several procedures to judge how extreme a particular outlier is. Data from the National Council Licensure EXamination (NCLEX) motivates our development and is used to illustrate the results.1 aBradlow, E T1 aWeiss, R E1 aCho, M uhttp://mail.iacat.org/content/bayesian-identification-outliers-computerized-adaptive-testing00497nas a2200109 4500008004100000245012000041210006900161260001400230100001200244700001200256856011900268 1998 eng d00aComparing and combining dichotomous and polytomous items with SPRT procedure in computerized classification testing0 aComparing and combining dichotomous and polytomous items with SP aSan Diego1 aLau, CA1 aWang, T uhttp://mail.iacat.org/content/comparing-and-combining-dichotomous-and-polytomous-items-sprt-procedure-computerized00581nas a2200121 4500008004100000245009500041210006900136260009200205100001300297700001500310700001800325856011600343 1998 eng d00aDeveloping, maintaining, and renewing the item inventory to support computer-based testing0 aDeveloping maintaining and renewing the item inventory to suppor aComputer-Based Testing: Building the Foundation for Future Assessments, Philadelphia PA1 aWay, W D1 aSteffen, M1 aAnderson, G S uhttp://mail.iacat.org/content/developing-maintaining-and-renewing-item-inventory-support-computer-based-testing00494nas a2200109 4500008004100000245007700041210006900118260006500187100001600252700001400268856010200282 1998 eng d00aDevelopment and evaluation of online calibration procedures (TCN 96-216)0 aDevelopment and evaluation of online calibration procedures TCN  aChampaign IL: Algorithm Design and Measurement Services, Inc1 aLevine, M L1 aWilliams. uhttp://mail.iacat.org/content/development-and-evaluation-online-calibration-procedures-tcn-96-21600466nas a2200121 4500008004100000245007700041210006900118260001400187100001200201700001100213700001600224856010400240 1998 eng d00aEssentially unbiased Bayesian estimates in computerized adaptive testing0 aEssentially unbiased Bayesian estimates in computerized adaptive aSan Diego1 aWang, T1 aLau, C1 aHanson, B A uhttp://mail.iacat.org/content/essentially-unbiased-bayesian-estimates-computerized-adaptive-testing00368nas a2200109 4500008004100000245005100041210005100092300001200143490000700155100001800162856007800180 1998 eng d00aPractical issues in computerized test assembly0 aPractical issues in computerized test assembly a292-3020 v221 aWightman, L F uhttp://mail.iacat.org/content/practical-issues-computerized-test-assembly00460nas a2200121 4500008004100000245007800041210006900119300001200188490000700200100001200207700001700219856010200236 1998 eng d00aProperties of ability estimation methods in computerized adaptive testing0 aProperties of ability estimation methods in computerized adaptiv a109-1350 v351 aWang, T1 aVispoel, W P uhttp://mail.iacat.org/content/properties-ability-estimation-methods-computerized-adaptive-testing00399nas a2200109 4500008004100000245006400041210006400105300001000169490001000179100001300189856008700202 1998 eng d00aProtecting the integrity of computerized testing item pools0 aProtecting the integrity of computerized testing item pools a17-270 v17(4)1 aWay, W D uhttp://mail.iacat.org/content/protecting-integrity-computerized-testing-item-pools01299nas a2200157 4500008004100000245007500041210006900116300001000185490000700195520076100202653003400963100001800997700001401015700001701029856009501046 1998 eng d00aSimulating the use of disclosed items in computerized adaptive testing0 aSimulating the use of disclosed items in computerized adaptive t a48-680 v353 aRegular use of questions previously made available to the public (i.e., disclosed items) may provide one way to meet the requirement for large numbers of questions in a continuous testing environment, that is, an environment in which testing is offered at test taker convenience throughout the year rather than on a few prespecified test dates. First it must be shown that such use has effects on test scores small enough to be acceptable. In this study simulations are used to explore the use of disclosed items under a worst-case scenario which assumes that disclosed items are always answered correctly. Some item pool and test designs were identified in which the use of disclosed items produces effects on test scores that may be viewed as negligible.10acomputerized adaptive testing1 aStocking, M L1 aWard, W C1 aPotenza, M T uhttp://mail.iacat.org/content/simulating-use-disclosed-items-computerized-adaptive-testing00558nas a2200145 4500008004100000245010200041210006900143300001000212490000700222100001600229700001600245700001400261700001400275856012300289 1998 eng d00aTesting word knowledge by telephone to estimate general cognitive aptitude using an adaptive test0 aTesting word knowledge by telephone to estimate general cognitiv a91-980 v261 aLegree, P J1 aFischl, M A1 aGade, P A1 aWilson, M uhttp://mail.iacat.org/content/testing-word-knowledge-telephone-estimate-general-cognitive-aptitude-using-adaptive-test00585nas a2200145 4500008004100000245011400041210006900155260001200224100001400236700001700250700001600267700001600283700001900299856012100318 1997 eng d00aThe accuracy of examinee judgments of relative item difficulty: Implication for computerized adaptive testing0 aaccuracy of examinee judgments of relative item difficulty Impli aChicago1 aWise, S L1 aFreeman, S A1 aFinney, S J1 aEnders, C K1 aSeverance, D D uhttp://mail.iacat.org/content/accuracy-examinee-judgments-relative-item-difficulty-implication-computerized-adaptive00536nas a2200121 4500008004100000245004000041210003900081260017700120100001400297700001600311700001700327856007000344 1997 eng d00aCAT-ASVAB cost and benefit analyses0 aCATASVAB cost and benefit analyses aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computer adaptive testing: From inquiry to operation (pp. 227-236). Washington, DC: American Psychological Association.1 aWise, L L1 aCurran, L T1 aMcBride, J R uhttp://mail.iacat.org/content/cat-asvab-cost-and-benefit-analyses00492nas a2200109 4500008004100000245010400041210006900145100001600214700002000230700001200250856012000262 1997 eng d00aComparability and validity of computerized adaptive testing with the MMPI-2 using a clinical sample0 aComparability and validity of computerized adaptive testing with1 aHandel, R W1 aBen-Porath, Y S1 aWatt, M uhttp://mail.iacat.org/content/comparability-and-validity-computerized-adaptive-testing-mmpi-2-using-clinical-sample00534nas a2200121 4500008004100000245013800041210006900179300001000248490000700258100001200265700001200277856012300289 1997 eng d00aComputerized adaptive and fixed-item testing of music listening skill: A comparison of efficiency, precision, and concurrent validity0 aComputerized adaptive and fixeditem testing of music listening s a43-630 v341 aVispoel1 aWang, T uhttp://mail.iacat.org/content/computerized-adaptive-and-fixed-item-testing-music-listening-skill-comparison-efficiency00568nas a2200133 4500008004100000245013800041210006900179300001000248490000700258100001700265700001200282700001500294856012500309 1997 eng d00aComputerized adaptive and fixed-item testing of music listening skill: A comparison of efficiency, precision, and concurrent validity0 aComputerized adaptive and fixeditem testing of music listening s a43-630 v341 aVispoel, W P1 aWang, T1 aBleiler, T uhttp://mail.iacat.org/content/computerized-adaptive-and-fixed-item-testing-music-listening-skill-comparison-efficiency-001687nam a2200145 4500008004100000245006100041210006000102260006200162520115300224653003401377100001501411700001601426700001701442856008201459 1997 eng d00aComputerized adaptive testing: From inquiry to operation0 aComputerized adaptive testing From inquiry to operation aWashington, D.C., USAbAmerican Psychological Association3 a(from the cover) This book traces the development of computerized adaptive testing (CAT) from its origins in the 1960s to its integration with the Armed Services Vocational Aptitude Battery (ASVAB) in the 1990s. A paper-and-pencil version of the battery (P&P-ASVAB) has been used by the Defense Department since the 1970s to measure the abilities of applicants for military service. The test scores are used both for initial qualification and for classification into entry-level training opportunities. /// This volume provides the developmental history of the CAT-ASVAB through its various stages in the Joint-Service arena. Although the majority of the book concerns the myriad technical issues that were identified and resolved, information is provided on various political and funding support challenges that were successfully overcome in developing, testing, and implementing the battery into one of the nation's largest testing programs. The book provides useful information to professionals in the testing community and everyone interested in personnel assessment and evaluation. (PsycINFO Database Record (c) 2004 APA, all rights reserved).10acomputerized adaptive testing1 aSands, W A1 aWaters, B K1 aMcBride, J R uhttp://mail.iacat.org/content/computerized-adaptive-testing-inquiry-operation00403nas a2200097 4500008004100000245007200041210006900113260001200182100001200194856009900206 1997 eng d00aEssentially unbiased EAP estimates in computerized adaptive testing0 aEssentially unbiased EAP estimates in computerized adaptive test aChicago1 aWang, T uhttp://mail.iacat.org/content/essentially-unbiased-eap-estimates-computerized-adaptive-testing00481nas a2200109 4500008004100000245010300041210006900144260001200213100001200225700001500237856011900252 1997 eng d00aEvaluating comparability in computerized adaptive testing: A theoretical framework with an example0 aEvaluating comparability in computerized adaptive testing A theo aChicago1 aWang, T1 aKolen, M J uhttp://mail.iacat.org/content/evaluating-comparability-computerized-adaptive-testing-theoretical-framework-example00276nas a2200097 4500008004100000245002700041210002700068260001500095100001400110856005400124 1997 eng d00aExaminee issues in CAT0 aExaminee issues in CAT aChicago IL1 aWise, S L uhttp://mail.iacat.org/content/examinee-issues-cat00513nas a2200145 4500008004100000245008100041210006900122300001200191490000700203100001500210700001400225700001200239700001600251856010000267 1997 eng d00aAn investigation of self-adapted testing in a Spanish high school population0 ainvestigation of selfadapted testing in a Spanish high school po a210-2210 v571 aPonsoda, V1 aWise, S L1 aOlea, J1 aRevuelta, J uhttp://mail.iacat.org/content/investigation-self-adapted-testing-spanish-high-school-population00413nas a2200121 4500008004100000245005400041210005400095260001500149100001600164700001600180700001800196856007700214 1997 eng d00aMaintaining a CAT item pool with operational data0 aMaintaining a CAT item pool with operational data aChicago IL1 aLevine, M L1 aSegall, D O1 aWilliams, B A uhttp://mail.iacat.org/content/maintaining-cat-item-pool-operational-data00340nas a2200097 4500008004100000245005000041210005000091260001500141100001400156856007200170 1997 eng d00aOverview of practical issues in a CAT program0 aOverview of practical issues in a CAT program aChicago IL1 aWise, S L uhttp://mail.iacat.org/content/overview-practical-issues-cat-program00665nas a2200121 4500008004100000245009200041210006900133260017800202100001700380700001600397700001600413856011400429 1997 eng d00aPreliminary psychometric research for CAT-ASVAB: Selecting an adaptive testing strategy0 aPreliminary psychometric research for CATASVAB Selecting an adap aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 83-95). Washington DC: American Psychological Association.1 aMcBride, J R1 aWetzel, C D1 aHetter, R D uhttp://mail.iacat.org/content/preliminary-psychometric-research-cat-asvab-selecting-adaptive-testing-strategy00336nas a2200097 4500008004100000245005000041210005000091260001500141100001300156856006900169 1997 eng d00aProtecting the integrity of the CAT item pool0 aProtecting the integrity of the CAT item pool aChicago IL1 aWay, W D uhttp://mail.iacat.org/content/protecting-integrity-cat-item-pool01815nas a2200169 4500008004100000245005300041210005300094250001000147260006000157300001000217520125400227653003401481100001701515700001601532700001701548856008001565 1997 eng d00aResearch antecedents of applied adaptive testing0 aResearch antecedents of applied adaptive testing axviii aWashington D.C. USAbAmerican Psychological Association a47-573 a(from the chapter) This chapter sets the stage for the entire computerized adaptive testing Armed Services Vocational Aptitude Battery (CAT-ASVAB) development program by describing the state of the art immediately preceding its inception. By the mid-l970s, a great deal of research had been conducted that provided the technical underpinnings needed to develop adaptive tests, but little research had been done to corroborate empirically the promising results of theoretical analyses and computer simulation studies. In this chapter, the author summarizes much of the important theoretical and simulation research prior to 1977. In doing so, he describes a variety of approaches to adaptive testing, and shows that while many methods for adaptive testing had been proposed, few practical attempts had been made to implement it. Furthermore, the few instances of adaptive testing were based primarily on traditional test theory, and were developed in laboratory settings for purposes of basic research. The most promising approaches, those based on item response theory and evaluated analytically or by means of computer simulations, remained to be proven in the crucible of live testing. (PsycINFO Database Record (c) 2004 APA, all rights reserved).10acomputerized adaptive testing1 aMcBride, J R1 aWaters, B K1 aMcBride, J R uhttp://mail.iacat.org/content/research-antecedents-applied-adaptive-testing00412nas a2200133 4500008004100000245005400041210004900095300001000144490000700154100001400161700001400175700001500189856007400204 1997 eng d00aThe role of item feedback in self-adapted testing0 arole of item feedback in selfadapted testing a85-980 v571 aRoos, L L1 aWise, S L1 aPlake, B S uhttp://mail.iacat.org/content/role-item-feedback-self-adapted-testing00543nas a2200121 4500008004100000245009900041210006900140260004600209100001800255700001400273700001700287856011700304 1997 eng d00aSimulating the use of disclosed items in computerized adaptive testing (Research Report 97-10)0 aSimulating the use of disclosed items in computerized adaptive t aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aWard, W C1 aPotenza, M T uhttp://mail.iacat.org/content/simulating-use-disclosed-items-computerized-adaptive-testing-research-report-97-1000648nas a2200133 4500008004100000245020300041210006900244260001600313100001700329700001700346700001200363700001700375856012200392 1996 eng d00aCan examinees use a review option to positively bias their scores on a computerized adaptive test? Paper presented at the annual meeting of the National council on Measurement in Education, New York0 aCan examinees use a review option to positively bias their score aNew York NY1 aRocklin, T R1 aVispoel, W P1 aWang, T1 aBleiler, T L uhttp://mail.iacat.org/content/can-examinees-use-review-option-positively-bias-their-scores-computerized-adaptive-test00485nas a2200133 4500008004100000245007400041210006900115300001000184490001000194100001700204700001700221700001400238856009900252 1996 eng d00aComputerized adaptive skill assessment in a statewide testing program0 aComputerized adaptive skill assessment in a statewide testing pr a49-670 v29(1)1 aShermis, M D1 aStemmer, P M1 aWebb, P M uhttp://mail.iacat.org/content/computerized-adaptive-skill-assessment-statewide-testing-program00447nas a2200145 4500008004100000245005100041210005000092300001200142490000700154100001400161700001400175700001400189700001700203856008100220 1996 eng d00aConducting self-adapted testing using MicroCAT0 aConducting selfadapted testing using MicroCAT a821-8270 v561 aRoos, L L1 aWise, S L1 aYoes, M E1 aRocklin, T R uhttp://mail.iacat.org/content/conducting-self-adapted-testing-using-microcat00451nas a2200097 4500008004100000245010100041210006900142260001300211100001400224856011500238 1996 eng d00aA critical analysis of the argument for and against item review in computerized adaptive testing0 acritical analysis of the argument for and against item review in aNew York1 aWise, S L uhttp://mail.iacat.org/content/critical-analysis-argument-and-against-item-review-computerized-adaptive-testing00551nas a2200109 4500008004100000245013000041210006900171260004600240100001700286700001300303856012500316 1996 eng d00aMissing responses and IRT ability estimation: Omits, choice, time limits, and adaptive testing (Research Report RR-96-30-ONR)0 aMissing responses and IRT ability estimation Omits choice time l aPrinceton NJ: Educational Testing Service1 aMislevy, R J1 aWu, P -K uhttp://mail.iacat.org/content/missing-responses-and-irt-ability-estimation-omits-choice-time-limits-and-adaptive-testing00466nas a2200121 4500008004100000245008000041210006900121260001300190100001300203700001200216700001300228856010300241 1996 eng d00aModifying the NCLEXTM CAT item selection algorithm to improve item exposure0 aModifying the NCLEXTM CAT item selection algorithm to improve it aNew York1 aWay, W D1 aZara, A1 aLeahy, J uhttp://mail.iacat.org/content/modifying-nclextm-cat-item-selection-algorithm-improve-item-exposure00433nas a2200121 4500008004100000245006500041210006500106260001400171100001300185700001200198700001300210856008800223 1996 eng d00aStrategies for managing item pools to maximize item security0 aStrategies for managing item pools to maximize item security aSan Diego1 aWay, W D1 aZara, A1 aLeahy, J uhttp://mail.iacat.org/content/strategies-managing-item-pools-maximize-item-security00534nas a2200121 4500008004100000245011800041210006900159260001800228100001300246700001300259700001500272856012500287 1995 eng d00aA comparison of two IRT-based models for computerized mastery testing when item parameter estimates are uncertain0 acomparison of two IRTbased models for computerized mastery testi aSan Francisco1 aWay, W D1 aLewis, C1 aSmith, R L uhttp://mail.iacat.org/content/comparison-two-irt-based-models-computerized-mastery-testing-when-item-parameter-estimates00506nas a2200133 4500008003900000245008900039210006900128300001200197490000700209100001300216700001600229700001700245856011000262 1995 d00aEffect of Rasch calibration on ability and DIF estimation in computer-adaptive tests0 aEffect of Rasch calibration on ability and DIF estimation in com a341-3630 v321 aZwick, R1 aThayer, D T1 aWingersky, M uhttp://mail.iacat.org/content/effect-rasch-calibration-ability-and-dif-estimation-computer-adaptive-tests00637nas a2200097 4500008004100000245010900041210006900150260018000219100001400399856012600413 1995 eng d00aImproving individual differences measurement with item response theory and computerized adaptive testing0 aImproving individual differences measurement with item response  aD. Lubinski and R. V. Dawis (Eds.), Assessing individual differences in human behavior: New concepts, methods, and findings (pp. 49-79). Palo Alto CA: Davies-Black Publishing.1 aWeiss, DJ uhttp://mail.iacat.org/content/improving-individual-differences-measurement-item-response-theory-and-computerized-adaptive00475nas a2200109 4500008004100000245009300041210006900134260002200203100001600225700001300241856011100254 1995 eng d00aAn investigation of item calibration procedures for a computerized licensure examination0 ainvestigation of item calibration procedures for a computerized  aSan Francisco, CA1 aHaynie, K A1 aWay, W D uhttp://mail.iacat.org/content/investigation-item-calibration-procedures-computerized-licensure-examination00400nas a2200097 4500008004100000245006700041210006700108260001900175100001400194856009400208 1995 eng d00aItem review and answer changing in computerized adaptive tests0 aItem review and answer changing in computerized adaptive tests aTrier, Germany1 aWise, S L uhttp://mail.iacat.org/content/item-review-and-answer-changing-computerized-adaptive-tests00496nas a2200109 4500008004100000245012300041210006900164300001200233490000600245100001100251856012400262 1995 eng d00aPrecision and differential item functioning on a testlet-based test: The 1991 Law School Admissions Test as an example0 aPrecision and differential item functioning on a testletbased te a157-1870 v81 aWainer uhttp://mail.iacat.org/content/precision-and-differential-item-functioning-testlet-based-test-1991-law-school-admissions00443nas a2200109 4500008004100000245007700041210006900118260001600187100001200203700001700215856010100232 1995 eng d00aPrecision of ability estimation methods in computerized adaptive testing0 aPrecision of ability estimation methods in computerized adaptive aMinneapolis1 aWang, T1 aVispoel, W P uhttp://mail.iacat.org/content/precision-ability-estimation-methods-computerized-adaptive-testing00490nam a2200097 4500008004100000245008100041210006900122260008600191100001200277856010300289 1995 eng d00aThe precision of ability estimation methods in computerized adaptive testing0 aprecision of ability estimation methods in computerized adaptive aUnpublished doctoral dissertation, University of Iowa, Iowa City (UM No. 9945102)1 aWang, T uhttp://mail.iacat.org/content/precision-ability-estimation-methods-computerized-adaptive-testing-000590nas a2200121 4500008004500000245017100045210006900216260001800285100001200303700001500315700001400330856012400344 1995 Spandsh 00aTests adaptivos y autoadaptados informatizados: Effects en la ansiedad y en la pecision de las estimaciones [SATs and CATS: Effects on enxiety and estimate precision]0 aTests adaptivos y autoadaptados informatizados Effects en la ans aMurcia, Spain1 aOlea, J1 aPonsoda, V1 aWise, S L uhttp://mail.iacat.org/content/tests-adaptivos-y-autoadaptados-informatizados-effects-en-la-ansiedad-y-en-la-pecision-de00535nas a2200121 4500008004100000245011500041210006900156260001900225100001400244700001400258700001500272856012600287 1994 eng d00aComparing computerized adaptive and self-adapted tests: The influence of examinee achievement locus of control0 aComparing computerized adaptive and selfadapted tests The influe aNew Orleans LA1 aWise, S L1 aRoos, L L1 aPlake, B S uhttp://mail.iacat.org/content/comparing-computerized-adaptive-and-self-adapted-tests-influence-examinee-achievement-locus00568nas a2200121 4500008004100000245011900041210006900160260004700229100001300276700001600289700001700305856012400322 1994 eng d00aDIF analysis for pretest items in computer-adaptive testing (Educational Testing Service Research Rep No RR 94-33)0 aDIF analysis for pretest items in computeradaptive testing Educa aPrinceton NJ: Educational Testing Service.1 aZwick, R1 aThayer, D T1 aWingersky, M uhttp://mail.iacat.org/content/dif-analysis-pretest-items-computer-adaptive-testing-educational-testing-service-research00461nas a2200109 4500008004100000245009400041210006900135260001600204100001600220700001300236856010200249 1994 eng d00aThe effects of item pool depth on the accuracy of pass/fail decisions for NCLEX using CAT0 aeffects of item pool depth on the accuracy of passfail decisions aNew Orleans1 aHaynie, K A1 aWay, W D uhttp://mail.iacat.org/content/effects-item-pool-depth-accuracy-passfail-decisions-nclex-using-cat00498nas a2200121 4500008004100000245009400041210006900135260002000204100001600224700001300240700001500253856010800268 1994 eng d00aEstablishing the comparability of the NCLEX using CAT with traditional NCLEX examinations0 aEstablishing the comparability of the NCLEX using CAT with tradi aNew Orleans, LA1 aEignor, D R1 aWay, W D1 aAmoss, K E uhttp://mail.iacat.org/content/establishing-comparability-nclex-using-cat-traditional-nclex-examinations00364nas a2200109 4500008004100000245004700041210004600088260001600134100001600150700001400166856007400180 1994 eng d00aEvaluation and implementation of CAT-ASVAB0 aEvaluation and implementation of CATASVAB aLos Angeles1 aCurran, L T1 aWise, L L uhttp://mail.iacat.org/content/evaluation-and-implementation-cat-asvab00572nas a2200133 4500008004100000245013900041210006900180300001000249490000600259100001700265700001700282700001200299856012700311 1994 eng d00aIndividual differences and test administration procedures: A comparison of fixed-item, computerized adaptive, and self-adapted testing0 aIndividual differences and test administration procedures A comp a53-790 v71 aVispoel, W P1 aRocklin, T R1 aWang, T uhttp://mail.iacat.org/content/individual-differences-and-test-administration-procedures-comparison-fixed-item-computerized00531nas a2200145 4500008004100000245008600041210006900127300001000196490000600206100001400212700001400226700001000240700002700250856010800277 1994 eng d00aThe relationship between examinee anxiety and preference for self-adapted testing0 arelationship between examinee anxiety and preference for selfada a81-910 v71 aWise, S L1 aRoos, L L1 aPlake1 aNebelsick-Gullett, L J uhttp://mail.iacat.org/content/relationship-between-examinee-anxiety-and-preference-self-adapted-testing00444nas a2200133 4500008004100000245005300041210005300094260002200147490000700169100001400176700002400190700001600214856008000230 1994 eng d00aReliability of alternate computer adaptive tests0 aReliability of alternate computer adaptive tests aNew JerseybAblex0 vII1 aLunz, M E1 aBergstrom, Betty, A1 aWright, B D uhttp://mail.iacat.org/content/reliability-alternate-computer-adaptive-tests00549nas a2200133 4500008004500000245010900045210006900154300001200223490000700235100001300242700001600255700001700271856012700288 1994 Engldsh 00aA Simulation Study of Methods for Assessing Differential Item Functioning in Computerized Adaptive Tests0 aSimulation Study of Methods for Assessing Differential Item Func a121-1400 v181 aZwick, R1 aThayer, D T1 aWingersky, M uhttp://mail.iacat.org/content/simulation-study-methods-assessing-differential-item-functioning-computerized-adaptive-tests00518nas a2200097 4500008004100000245012400041210006900165260004600234100001300280856012700293 1994 eng d00aA simulation study of the Mantel-Haenszel procedure for detecting DIF with the NCLEX using CAT (Technical Report xx-xx)0 asimulation study of the MantelHaenszel procedure for detecting D aPrinceton NJ: Educational Testing Service1 aWay, W D uhttp://mail.iacat.org/content/simulation-study-mantel-haenszel-procedure-detecting-dif-nclex-using-cat-technical-report-xx00421nas a2200109 4500008004100000245007300041210006900114300001000183490000600193100001400199856009800213 1994 eng d00aUnderstanding self-adapted testing: The perceived control hypothesis0 aUnderstanding selfadapted testing The perceived control hypothes a15-240 v71 aWise, S L uhttp://mail.iacat.org/content/understanding-self-adapted-testing-perceived-control-hypothesis00569nas a2200133 4500008004100000245009600041210006900137260004600206100001600252700001800268700001300286700001500299856012100314 1993 eng d00aCase studies in computer adaptive test design through simulation (Research Report RR-93-56)0 aCase studies in computer adaptive test design through simulation aPrinceton NJ: Educational Testing Service1 aEignor, D R1 aStocking, M L1 aWay, W D1 aSteffen, M uhttp://mail.iacat.org/content/case-studies-computer-adaptive-test-design-through-simulation-research-report-rr-93-5600569nas a2200133 4500008004100000245009700041210006900138260004600207100001600253700001300269700001600282700001500298856012200313 1993 eng d00aCase studies in computerized adaptive test design through simulation (Research Report 93-56)0 aCase studies in computerized adaptive test design through simula aPrinceton NJ: Educational Testing Service1 aEignor, D R1 aWay, W D1 aStocking, M1 aSteffen, M uhttp://mail.iacat.org/content/case-studies-computerized-adaptive-test-design-through-simulation-research-report-93-5600413nas a2200121 4500008004100000245006000041210006000101300001000161490001000171100001000181700001300191856008700204 1993 eng d00aComputerized adaptive testing in instructional settings0 aComputerized adaptive testing in instructional settings a47-620 v41(3)1 aWelch1 aFrick, T uhttp://mail.iacat.org/content/computerized-adaptive-testing-instructional-settings00534nas a2200121 4500008004100000245011600041210006900157260001500226100001700241700001200258700001500270856012700285 1993 eng d00aThe efficiency, reliability, and concurrent validity of adaptive and fixed-item tests of music listening skills0 aefficiency reliability and concurrent validity of adaptive and f aAtlanta GA1 aVispoel, W P1 aWang, T1 aBleiler, T uhttp://mail.iacat.org/content/efficiency-reliability-and-concurrent-validity-adaptive-and-fixed-item-tests-music-listening00415nas a2200121 4500008004100000245005600041210005200097260001500149100001400164700001900178700001600197856008000213 1993 eng d00aAn investigation of restricted self-adapted testing0 ainvestigation of restricted selfadapted testing aAtlanta GA1 aWise, S L1 aKingsbury, G G1 aHouser, R L uhttp://mail.iacat.org/content/investigation-restricted-self-adapted-testing00606nas a2200121 4500008004100000245016000041210006900201260004700270100001300317700001400330700001700344856012300361 1993 eng d00aA simulation study of methods for assessing differential item functioning in computer-adaptive tests (Educational Testing Service Research Rep No RR 93-11)0 asimulation study of methods for assessing differential item func aPrinceton NJ: Educational Testing Service.1 aZwick, R1 aThayer, D1 aWingersky, M uhttp://mail.iacat.org/content/simulation-study-methods-assessing-differential-item-functioning-computer-adaptive-tests00476nas a2200109 4500008004100000245010100041210006900142300001000211490001100221100001100232856012300243 1993 eng d00aSome practical considerations when converting a linearly administered test to an adaptive format0 aSome practical considerations when converting a linearly adminis a15-200 v12 (1)1 aWainer uhttp://mail.iacat.org/content/some-practical-considerations-when-converting-linearly-administered-test-adaptive-format00514nas a2200145 4500008004100000245007700041210006900118300001200187490000700199100001400206700001500220700001700235700001400252856010200266 1992 eng d00aA comparison of self-adapted and computerized adaptive achievement tests0 acomparison of selfadapted and computerized adaptive achievement  a329-3390 v291 aWise, S L1 aPlake, S S1 aJohnson, P L1 aRoos, S L uhttp://mail.iacat.org/content/comparison-self-adapted-and-computerized-adaptive-achievement-tests00483nas a2200133 4500008004100000245008200041210006900123300001200192490000700204100001100211700001400222700001300236856010000249 1992 eng d00aA comparison of the performance of simulated hierarchical and linear testlets0 acomparison of the performance of simulated hierarchical and line a243-2510 v291 aWainer1 aKaplan, B1 aLewis, C uhttp://mail.iacat.org/content/comparison-performance-simulated-hierarchical-and-linear-testlets00523nas a2200133 4500008004500000245009600045210006900141300001000210490000700220100001400227700001800241700001600259856011400275 1992 Engldsh 00aThe Effect of Review on Student Ability and Test Efficiency for Computerized Adaptive Tests0 aEffect of Review on Student Ability and Test Efficiency for Comp a33-400 v161 aLunz, M E1 aBerstrom, B A1 aWright, B D uhttp://mail.iacat.org/content/effect-review-student-ability-and-test-efficiency-computerized-adaptive-tests-001336nas a2200145 4500008004100000245009600041210006900137300001000206490000700216520079300223100001401016700002401030700002401054856011201078 1992 eng d00aThe effect of review on student ability and test efficiency for computerized adaptive tests0 aeffect of review on student ability and test efficiency for comp a33-400 v163 a220 students were randomly assigned to a review condition for a medical technology test; their test instructions indicated that each item must be answered when presented, but that the responses could be reviewed and altered at the end of the test. A sample of 492 students did not have the opportunity to review and alter responses. Within the review condition, examinee ability estimates before and after review were correlated .98. The average efficiency of the test was decreased by 1% after review. Approximately 32% of the examinees improved their ability estimates after review but did not change their pass/fail status. Disallowing review on adaptive tests administered under these rules is not supported by these data. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aLunz, M E1 aBergstrom, Betty, A1 aWright, Benjamin, D uhttp://mail.iacat.org/content/effect-review-student-ability-and-test-efficiency-computerized-adaptive-tests00465nas a2200121 4500008004100000245007600041210006900117260001800186100001400204700001500218700001400233856009600247 1992 eng d00aThe effects of feedback in computerized adaptive and self-adapted tests0 aeffects of feedback in computerized adaptive and selfadapted tes aSan Francisco1 aRoos, L L1 aPlake, B S1 aWise, S L uhttp://mail.iacat.org/content/effects-feedback-computerized-adaptive-and-self-adapted-tests00573nas a2200121 4500008004100000245013200041210006900173260004700242100001200289700001700301700001100318856012200329 1992 eng d00aA general Bayesian model for testlets: theory and applications (Research Report 92-21; GRE Board Professional Report No 99-01P)0 ageneral Bayesian model for testlets theory and applications Rese aPrinceton NJ: Educational Testing Service.1 aWang, X1 aBradlow, E T1 aWainer uhttp://mail.iacat.org/content/general-bayesian-model-testlets-theory-and-applications-research-report-92-21-gre-board00574nas a2200145 4500008004100000245009700041210006900138260002100207100001700228700001200245700001900257700001500276700001300291856012400304 1992 eng d00aHow review options and administration mode influence scores on computerized vocabulary tests0 aHow review options and administration mode influence scores on c aSan Francisco CA1 aVispoel, W P1 aWang, T1 aDe la Torre, R1 aBleiler, T1 aDings, J uhttp://mail.iacat.org/content/how-review-options-and-administration-mode-influence-scores-computerized-vocabulary-tests00434nas a2200109 4500008004100000245007200041210006900113260001800182100001200200700001700212856009500229 1992 eng d00aIncorporating post-administration item response revision into a CAT0 aIncorporating postadministration item response revision into a C aSan Francisco1 aWang, M1 aWingersky, M uhttp://mail.iacat.org/content/incorporating-post-administration-item-response-revision-cat00522nas a2200097 4500008004100000245013200041210006900173260004600242100001100288856012500299 1992 eng d00aSome practical considerations when converting a linearly administered test to an adaptive format (Research Report 92-21 or 13?)0 aSome practical considerations when converting a linearly adminis aPrinceton NJ: Educational Testing Service1 aWainer uhttp://mail.iacat.org/content/some-practical-considerations-when-converting-linearly-administered-test-adaptive-format-000516nas a2200145 4500008004100000245008200041210006900123300001200192490000600204100001100210700001300221700001400234700001600248856010600264 1991 eng d00aBuilding algebra testlets: A comparison of hierarchical and linear structures0 aBuilding algebra testlets A comparison of hierarchical and linea axxx-xxx0 v81 aWainer1 aLewis, C1 aKaplan, B1 aBraswell, J uhttp://mail.iacat.org/content/building-algebra-testlets-comparison-hierarchical-and-linear-structures00500nas a2200145 4500008004100000245007200041210006900113300001000182490000600192100001700198700001400215700001400229700001500243856009600258 1991 eng d00aCorrelates of examinee item choice behavior in self-adapted testing0 aCorrelates of examinee item choice behavior in selfadapted testi a25-280 v41 aJohnson, J L1 aRoos, L L1 aWise, S L1 aPlake, B S uhttp://mail.iacat.org/content/correlates-examinee-item-choice-behavior-self-adapted-testing00386nas a2200133 4500008004100000245004600041210003800087300001200125490000700137100001600144700001100160700001500171856006600186 1991 eng d00aOn the reliability of testlet-based tests0 areliability of testletbased tests a237-2470 v281 aSireci, S G1 aWainer1 aThissen, D uhttp://mail.iacat.org/content/reliability-testlet-based-tests00523nas a2200121 4500008004100000245007700041210006900118260007500187100001100262700001400273700001300287856010100300 1991 eng d00aSome empirical guidelines for building testlets (Technical Report 91-56)0 aSome empirical guidelines for building testlets Technical Report aPrinceton NJ: Educational Testing Service, Program Statistics Research1 aWainer1 aKaplan, B1 aLewis, C uhttp://mail.iacat.org/content/some-empirical-guidelines-building-testlets-technical-report-91-5600556nas a2200133 4500008004100000245010600041210006900147260003100216100001100247700001300258700001100271700001600282856012400298 1990 eng d00aAn adaptive algebra test: A testlet-based, hierarchically structured test with validity-based scoring0 aadaptive algebra test A testletbased hierarchically structured t aETS Technical Report 90-921 aWainer1 aLewis, C1 aKaplan1 aBraswell, J uhttp://mail.iacat.org/content/adaptive-algebra-test-testlet-based-hierarchically-structured-test-validity-based-scoring00516nam a2200169 4500008003900000245005100039210004700090260002600137100001100163700001600174700001600190700001400206700001700220700001700237700001500254856007700269 1990 d00aComputerized adaptive testing: A primer (Eds.)0 aComputerized adaptive testing A primer Eds aHillsdale NJ: Erlbaum1 aWainer1 aDorans, N J1 aFlaugher, R1 aGreen, BF1 aMislevy, R J1 aSteinberg, L1 aThissen, D uhttp://mail.iacat.org/content/computerized-adaptive-testing-primer-eds-200484nas a2200157 4500008004100000245002200041210002200063260009900085100001100184700001600195700001400211700001700225700001700242700001500259856005200274 1990 eng d00aFuture challenges0 aFuture challenges aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 233-272). Hillsdale NJ: Erlbaum.1 aWainer1 aDorans, N J1 aGreen, BF1 aMislevy, R J1 aSteinberg, L1 aThissen, D uhttp://mail.iacat.org/content/future-challenges00463nas a2200109 4500008004100000245005400041210005400095260009400149100001500243700001600258856007900274 1990 eng d00aGenerative adaptive testing with digit span items0 aGenerative adaptive testing with digit span items aSan Diego, CA: Testing Systems Department, Navy Personnel Research and Development Center1 aWolfe, J H1 aLarson, G E uhttp://mail.iacat.org/content/generative-adaptive-testing-digit-span-items00347nas a2200097 4500008004100000245002800041210002800069260008600097100001100183856005500194 1990 eng d00aImportant issues in CAT0 aImportant issues in CAT aH. Wainer et al., Computerized adaptive testing: A primer. Hillsdale NJ: Erlbaum.1 aWainer uhttp://mail.iacat.org/content/important-issues-cat00368nas a2200097 4500008004100000245002900041210002900070260010100099100001100200856005900211 1990 eng d00aIntroduction and history0 aIntroduction and history aIn H. Wainer (Ed.), Computerized adaptive testing: A Primer (pp. 1 - 21). Hillsdale NJ: Erlbaum.1 aWainer uhttp://mail.iacat.org/content/introduction-and-history00516nas a2200109 4500008004100000245007100041210006900112260009800181100001100279700001700290856009900307 1990 eng d00aItem response theory, item calibration, and proficiency estimation0 aItem response theory item calibration and proficiency estimation aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 65-102). Hillsdale NJ: Erlbaum.1 aWainer1 aMislevy, R J uhttp://mail.iacat.org/content/item-response-theory-item-calibration-and-proficiency-estimation00379nas a2200109 4500008004100000245002300041210002300064260009900087100001100186700001700197856005500214 1990 eng d00aTesting algorithms0 aTesting algorithms aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 103-135). Hillsdale NJ: Erlbaum.1 aWainer1 aMislevy, R J uhttp://mail.iacat.org/content/testing-algorithms-000347nas a2200121 4500008004100000245004000041210004000081300000900121490000700130100001100137700001300148856006400161 1990 eng d00aToward a psychometrics for testlets0 aToward a psychometrics for testlets a1-140 v271 aWainer1 aLewis, C uhttp://mail.iacat.org/content/toward-psychometrics-testlets00374nas a2200121 4500008004100000245001300041210001300054260009900067100001700166700001500183700001100198856004300209 1990 eng d00aValidity0 aValidity aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 187-231). Hillsdale NJ: Erlbaum.1 aSteinberg, L1 aThissen, D1 aWainer uhttp://mail.iacat.org/content/validity00400nam a2200097 4500008004100000245004900041210004900090260006800139100001600207856007900223 1989 eng d00aComputerized adaptive personality assessment0 aComputerized adaptive personality assessment aUnpublished master’s thesis, Harvard University, Cambridge MA1 aWaller, N G uhttp://mail.iacat.org/content/computerized-adaptive-personality-assessment00397nas a2200121 4500008004100000245003200041210003200073260007000105100001300175700001600188700000900204856006200213 1989 eng d00aComputerized adaptive tests0 aComputerized adaptive tests aERIC Clearinghouse on Tests, Measurement, and Evaluation, no. 1071 aGrist, S1 aRudner, L M1 aWise uhttp://mail.iacat.org/content/computerized-adaptive-tests00453nas a2200097 4500008004100000245007900041210006900120260004600189100001900235856010100254 1989 eng d00aA consideration for variable length adaptive tests (Research Report 89-40)0 aconsideration for variable length adaptive tests Research Report aPrinceton NJ: Educational Testing Service1 aWingersky, M S uhttp://mail.iacat.org/content/consideration-variable-length-adaptive-tests-research-report-89-4000511nas a2200133 4500008004100000245009200041210006900133300001200202490000700214100001400221700001500235700001200250856011500262 1989 eng d00aProviding item feedback in computer-based tests: Effects of initial success and failure0 aProviding item feedback in computerbased tests Effects of initia a479-4860 v491 aWise, S L1 aPlake, B S1 aet. al. uhttp://mail.iacat.org/content/providing-item-feedback-computer-based-tests-effects-initial-success-and-failure00487nas a2200121 4500008004100000245009400041210006900135300001000204490000700214100001700221700001400238856011300252 1988 eng d00aAssessment of academic skills of learning disabled students with classroom microcomputers0 aAssessment of academic skills of learning disabled students with a81-880 v171 aWatkins, M W1 aKush, J C uhttp://mail.iacat.org/content/assessment-academic-skills-learning-disabled-students-classroom-microcomputers00471nas a2200109 4500008004100000245010000041210006900141300001200210490000600222100001400228856011900242 1988 eng d00aThe College Board computerized placement tests: An application of computerized adaptive testing0 aCollege Board computerized placement tests An application of com a271-2820 v21 aWard, W C uhttp://mail.iacat.org/content/college-board-computerized-placement-tests-application-computerized-adaptive-testing00525nas a2200133 4500008004100000245009300041210006900134260001500203100002000218700001600238700001700254700001700271856010300288 1988 eng d00aA comparison of two methods for the adaptive administration of the MMPI-2 content scales0 acomparison of two methods for the adaptive administration of the aAtlanta GA1 aBen-Porath, Y S1 aWaller, N G1 aSlutske, W S1 aButcher, J N uhttp://mail.iacat.org/content/comparison-two-methods-adaptive-administration-mmpi-2-content-scales00492nas a2200097 4500008004100000245012800041210006900169100001500238700001600253856012500269 1988 eng d00aFitting the two-parameter model to personality data: The parameterization of the Multidimensional Personality Questionnaire0 aFitting the twoparameter model to personality data The parameter1 aReise, S P1 aWaller, N G uhttp://mail.iacat.org/content/fitting-two-parameter-model-personality-data-parameterization-multidimensional-personality00623nas a2200145 4500008004100000245011100041210006900152260005400221100001400275700001700289700001400306700001600320700001700336856012400353 1988 eng d00aRefinement of the Computerized Adaptive Screening Test (CAST) (Final Report, Contract No MDA203 06-C-0373)0 aRefinement of the Computerized Adaptive Screening Test CAST Fina aWashington, DC: American Institutes for Research.1 aWise, L L1 aMcHenry, J J1 aChia, W J1 aSzenas, P L1 aMcBride, J R uhttp://mail.iacat.org/content/refinement-computerized-adaptive-screening-test-cast-final-report-contract-no-mda203-06-c00303nas a2200121 4500008004100000245002100041210002100062300001200083490000700095100001400102700001400116856005100130 1987 eng d00aAdaptive testing0 aAdaptive testing a249-2620 v361 aWeiss, DJ1 aVale, C D uhttp://mail.iacat.org/content/adaptive-testing00487nas a2200121 4500008004100000245009700041210006900138300001200207490000700219100001100226700001500237856011300252 1987 eng d00aCATS, testlets, and test construction: A rationale for putting test developers back into CAT0 aCATS testlets and test construction A rationale for putting test a185-2020 v321 aWainer1 aKiely, G L uhttp://mail.iacat.org/content/cats-testlets-and-test-construction-rationale-putting-test-developers-back-cat00581nas a2200109 4500008004100000245009200041210006900133260012300202100001400325700001400339856011800353 1987 eng d00aComputerized adaptive testing for measuring abilities and other psychological variables0 aComputerized adaptive testing for measuring abilities and other  aJ. N. Butcher (Ed.), Computerized personality measurement: A practitioners guide (pp. 325-343). New York: Basic Books.1 aWeiss, DJ1 aVale, C D uhttp://mail.iacat.org/content/computerized-adaptive-testing-measuring-abilities-and-other-psychological-variables00474nas a2200121 4500008004100000245008200041210006900123260001300192100001700205700001500222700001200237856010300249 1987 eng d00aEquating the computerized adaptive edition of the Differential Aptitude Tests0 aEquating the computerized adaptive edition of the Differential A aNew York1 aMcBride, J R1 aCorpe, V A1 aWing, H uhttp://mail.iacat.org/content/equating-computerized-adaptive-edition-differential-aptitude-tests-000444nas a2200121 4500008003900000245007300039210006900112300001200181490000700193100001100200700001500211856009600226 1987 d00aItem clusters and computerized adaptive testing: A case for testlets0 aItem clusters and computerized adaptive testing A case for testl a185-2010 v241 aWainer1 aKiely, G L uhttp://mail.iacat.org/content/item-clusters-and-computerized-adaptive-testing-case-testlets00566nas a2200109 4500008004100000245012200041210006900163260007500232100001100307700001500318856012300333 1986 eng d00aCATs, testlets, and test construction: A rationale for putting test developers back into CAT (Technical Report 86-71)0 aCATs testlets and test construction A rationale for putting test aPrinceton NJ: Educational Testing Service, Program Statistics Research1 aWainer1 aKiely, G L uhttp://mail.iacat.org/content/cats-testlets-and-test-construction-rationale-putting-test-developers-back-cat-technical00568nas a2200121 4500008004100000245011900041210006900160260004800229100001400277700001500291700001600306856012400322 1986 eng d00aCollege Board computerized placement tests: Validation of an adaptive test of basic skills (Research Report 86-29)0 aCollege Board computerized placement tests Validation of an adap aPrinceton NJ: Educational Testing Service.1 aWard, W C1 aKline, R G1 aFlaugher, J uhttp://mail.iacat.org/content/college-board-computerized-placement-tests-validation-adaptive-test-basic-skills-research00320nas a2200109 4500008004100000245003600041210003600077300001000113490000600123100001500129856006600144 1986 eng d00aComputerized testing technology0 aComputerized testing technology a71-780 v41 aWolfe, J H uhttp://mail.iacat.org/content/computerized-testing-technology00310nas a2200109 4500008004100000245003300041210003300074300001200107490000700119100001400126856006000140 1985 eng d00aAdaptive testing by computer0 aAdaptive testing by computer a774-7890 v531 aWeiss, DJ uhttp://mail.iacat.org/content/adaptive-testing-computer00624nas a2200133 4500008004100000245012600041210006900167260006700236100001900303700001400322700001600336700001500352856012300367 1985 eng d00aArmed Services Vocational Aptitude Battery: Development of an adaptive item pool (AFHLR-TR-85-19; Technical Rep No 85-19)0 aArmed Services Vocational Aptitude Battery Development of an ada aBrooks Air Force Base TX: Air Force Human Resources Laboratory1 aPrestwood, J S1 aVale, C D1 aMassey, R H1 aWelsh, J R uhttp://mail.iacat.org/content/armed-services-vocational-aptitude-battery-development-adaptive-item-pool-afhlr-tr-85-1900503nas a2200097 4500008004100000245007900041210006900120260009700189100001400286856010500300 1985 eng d00aFinal report: Computerized adaptive measurement of achievement and ability0 aFinal report Computerized adaptive measurement of achievement an aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ uhttp://mail.iacat.org/content/final-report-computerized-adaptive-measurement-achievement-and-ability00381nas a2200097 4500008004100000245001700041210001700058260014700075100001400222856004700236 1985 eng d00aIntroduction0 aIntroduction aIn D. J. Weiss (Ed.), New horizons in testing: Latent trait test theory and computerized adaptive testing (pp. 1-8). New York: Academic Press.1 aWeiss, DJ uhttp://mail.iacat.org/content/introduction00492nam a2200097 4500008004100000245006900041210006900110260010900179100001400288856009200302 1985 eng d00aProceedings of the 1982 Computerized Adaptive Testing Conference0 aProceedings of the 1982 Computerized Adaptive Testing Conference aMinneapolis: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://mail.iacat.org/content/proceedings-1982-computerized-adaptive-testing-conference00485nas a2200109 4500008004100000245005900041210005900100260010100159100001600260700001700276856008200293 1985 eng d00aReducing the predictability of adaptive item sequences0 aReducing the predictability of adaptive item sequences aProceedings of the 27th Annual Conference of the Military Testing Association, San Diego, 43-48.1 aWetzel, C D1 aMcBride, J R uhttp://mail.iacat.org/content/reducing-predictability-adaptive-item-sequences00407nas a2200121 4500008004500000245005400045210005400099300001200153490000600165100001400171700001700185856008300202 1984 Engldsh 00aBias and Information of Bayesian Adaptive Testing0 aBias and Information of Bayesian Adaptive Testing a273-2850 v81 aWeiss, DJ1 aMcBride, J R uhttp://mail.iacat.org/content/bias-and-information-bayesian-adaptive-testing-000401nas a2200121 4500008004100000245005400041210005400095300001200149490000600161100001400167700001700181856008100198 1984 eng d00aBias and information of Bayesian adaptive testing0 aBias and information of Bayesian adaptive testing a273-2850 v81 aWeiss, DJ1 aMcBride, J R uhttp://mail.iacat.org/content/bias-and-information-bayesian-adaptive-testing00541nas a2200133 4500008004100000245007700041210006900118260006500187100001200252700001400264700001500278700001500293856009900308 1984 eng d00aMicrocomputer network for computerized adaptive testing (CAT) (TR-84-33)0 aMicrocomputer network for computerized adaptive testing CAT TR84 aSan Diego CA: Navy Personnel Research and Development Center1 aQuan, B1 aPark, T A1 aSandahl, G1 aWolfe, J H uhttp://mail.iacat.org/content/microcomputer-network-computerized-adaptive-testing-cat-tr-84-3300501nas a2200121 4500008004100000245009200041210006900133260001900202100001700221700001400238700001300252856011400265 1984 eng d00aPredictive validity of computerized adaptive testing in a military training environment0 aPredictive validity of computerized adaptive testing in a milita aNew Orleans LA1 aSympson, J B1 aWeiss, DJ1 aRee, M J uhttp://mail.iacat.org/content/predictive-validity-computerized-adaptive-testing-military-training-environment00604nas a2200145 4500008004500000245013900045210006900184300001200253490000600265100001600271700001600287700001700303700001400320856012400334 1984 Engldsh 00aRelationship Between Corresponding Armed Services Vocational Aptitude Battery (ASVAB) and Computerized Adaptive Testing (CAT) Subtests0 aRelationship Between Corresponding Armed Services Vocational Apt a155-1630 v81 aMoreno, K E1 aWetzel, C D1 aMcBride, J R1 aWeiss, DJ uhttp://mail.iacat.org/content/relationship-between-corresponding-armed-services-vocational-aptitude-battery-asvab-and-101571nas a2200169 4500008004100000245013900041210006900180300001200249490000600261520091500267653003401182100001601216700001601232700001701248700001401265856012201279 1984 eng d00aRelationship between corresponding Armed Services Vocational Aptitude Battery (ASVAB) and computerized adaptive testing (CAT) subtests0 aRelationship between corresponding Armed Services Vocational Apt a155-1630 v83 aInvestigated the relationships between selected subtests from the Armed Services Vocational Aptitude Battery (ASVAB) and corresponding subtests administered as computerized adaptive tests (CATs), using 270 17-26 yr old Marine recruits as Ss. Ss were administered the ASVAB before enlisting and approximately 2 wks after entering active duty, and the CAT tests were administered to Ss approximately 24 hrs after arriving at the recruit depot. Results indicate that 3 adaptive subtests correlated as well with ASVAB as did the 2nd administration of the ASVAB, although CAT subtests contained only half the number of items. Factor analysis showed CAT subtests to load on the same factors as the corresponding ASVAB subtests, indicating that the same abilities were being measured. It is concluded that CAT can achieve the same measurement precision as a conventional test, with half the number of items. (16 ref) 10acomputerized adaptive testing1 aMoreno, K E1 aWetzel, C D1 aMcBride, J R1 aWeiss, DJ uhttp://mail.iacat.org/content/relationship-between-corresponding-armed-services-vocational-aptitude-battery-asvab-and00346nas a2200109 4500008004100000245004500041210004500086300001000131490000900141100001400150856007200164 1984 eng d00aUsing microcomputers to administer tests0 aUsing microcomputers to administer tests a16-200 v3(2)1 aWard, W C uhttp://mail.iacat.org/content/using-microcomputers-administer-tests00626nas a2200121 4500008004100000245011400041210006900155260011200224100001500336700001200351700001400363856012700377 1983 eng d00aAlternate forms reliability and concurrent validity of adaptive and conventional tests with military recruits0 aAlternate forms reliability and concurrent validity of adaptive  aMinneapolis MN: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aKiely, G L1 aZara, A1 aWeiss, DJ uhttp://mail.iacat.org/content/alternate-forms-reliability-and-concurrent-validity-adaptive-and-conventional-tests-military00539nas a2200109 4500008004100000245007700041210006900118260010900187100001400296700001700310856010200327 1983 eng d00aBias and information of Bayesian adaptive testing (Research Report 83-2)0 aBias and information of Bayesian adaptive testing Research Repor aMinneapolis: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ1 aMcBride, J R uhttp://mail.iacat.org/content/bias-and-information-bayesian-adaptive-testing-research-report-83-200614nas a2200109 4500008004100000245009800041210006900139260013900208100002000347700001400367856012300381 1983 eng d00aA comparison of IRT-based adaptive mastery testing and a sequential mastery testing procedure0 acomparison of IRTbased adaptive mastery testing and a sequential aD. J. Weiss (Ed.), New horizons in testing: Latent trait theory and computerized adaptive testing (pp. 1-8). New York: Academic Press.1 aKingsbury, G.G.1 aWeiss, DJ uhttp://mail.iacat.org/content/comparison-irt-based-adaptive-mastery-testing-and-sequential-mastery-testing-procedure-100622nas a2200109 4500008004100000245009800041210006900139260014800208100001900356700001400375856012300389 1983 eng d00aA comparison of IRT-based adaptive mastery testing and a sequential mastery testing procedure0 acomparison of IRTbased adaptive mastery testing and a sequential aD. J. Weiss (Ed.), New horizons in testing: Latent trait test theory and computerized adaptive testing (pp. 257-283). New York: Academic Press.1 aKingsbury, G G1 aWeiss, DJ uhttp://mail.iacat.org/content/comparison-irt-based-adaptive-mastery-testing-and-sequential-mastery-testing-procedure-000536nas a2200121 4500008004100000245009900041210006900140260003900209300001200248100001900260700001400279856012100293 1983 eng d00aA comparison of IRT-based adaptive mastery testing and a sequential mastery testing procedure.0 acomparison of IRTbased adaptive mastery testing and a sequential aNew York, NY. USAbAcademic Press. a258-2831 aKingsbury, G G1 aWeiss, DJ uhttp://mail.iacat.org/content/comparison-irt-based-adaptive-mastery-testing-and-sequential-mastery-testing-procedure00493nas a2200097 4500008004100000245007400041210006900115260009700184100001400281856010000295 1983 eng d00aFinal report: Computer-based measurement of intellectual capabilities0 aFinal report Computerbased measurement of intellectual capabilit aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ uhttp://mail.iacat.org/content/final-report-computer-based-measurement-intellectual-capabilities00548nas a2200109 4500008004100000245010400041210006900145260006600214100001600280700001700296856012500313 1983 eng d00aInfluence of fallible item parameters on test information during adaptive testing (Tech Rep 83-15).0 aInfluence of fallible item parameters on test information during aSan Diego CA: Navy Personnel Research and Development Center.1 aWetzel, C D1 aMcBride, J R uhttp://mail.iacat.org/content/influence-fallible-item-parameters-test-information-during-adaptive-testing-tech-rep-83-1500478nas a2200109 4500008004100000245010600041210006900147300000900216490000700225100001100232856012500243 1983 eng d00aOn item response theory and computerized adaptive testing: The coming technical revolution in testing0 aitem response theory and computerized adaptive testing The comin a9-160 v281 aWainer uhttp://mail.iacat.org/content/item-response-theory-and-computerized-adaptive-testing-coming-technical-revolution-testing00453nam a2200097 4500008004100000245008800041210006900129260002900198100001400227856011400241 1983 eng d00aNew horizons in testing: Latent trait test theory and computerized adaptive testing0 aNew horizons in testing Latent trait test theory and computerize aNew York: Academic Press1 aWeiss, DJ uhttp://mail.iacat.org/content/new-horizons-testing-latent-trait-test-theory-and-computerized-adaptive-testing00578nas a2200109 4500008004100000245008100041210006900122260014700191100001600338700001400354856010000368 1983 eng d00aThe person response curve: Fit of individuals to item response theory models0 aperson response curve Fit of individuals to item response theory aD. J. Weiss (Ed.), New horizons in testing: Latent trait test theory and computerized adaptive testing (pp. 83-108). New York: Academic Press.1 aTrabin, T E1 aWeiss, DJ uhttp://mail.iacat.org/content/person-response-curve-fit-individuals-item-response-theory-models00480nas a2200109 4500008004100000245008400041210006900125260004100194100001700235700001500252856010300267 1983 eng d00aPredictive utility evaluation of adaptive testing: Results of the Navy research0 aPredictive utility evaluation of adaptive testing Results of the aFalls Church VA: The Rehab Group Inc1 aHardwicke, S1 aWhite, K E uhttp://mail.iacat.org/content/predictive-utility-evaluation-adaptive-testing-results-navy-research00646nas a2200133 4500008004100000245015000041210006900191260006500260100001600325700001600341700001700357700001400374856012400388 1983 eng d00aRelationship between corresponding Armed Services Vocational Aptitude Battery (ASVAB) and computerized adaptive testing (CAT) subtests (TR 83-27)0 aRelationship between corresponding Armed Services Vocational Apt aSan Diego CA: Navy Personnel Research and Development Center1 aMoreno, K E1 aWetzel, D C1 aMcBride, J R1 aWeiss, DJ uhttp://mail.iacat.org/content/relationship-between-corresponding-armed-services-vocational-aptitude-battery-asvab-and-000621nas a2200121 4500008004100000245011100041210006900152260010500221100001700326700001600343700001400359856012600373 1983 eng d00aReliability and validity of adaptive ability tests in a military recruit population (Research Report 83-1)0 aReliability and validity of adaptive ability tests in a military aMinneapolis: Department of Psychology, Psychometric Methods Program, Computerized Testing Laboratory1 aMcBride, J R1 aMartin, J T1 aWeiss, DJ uhttp://mail.iacat.org/content/reliability-and-validity-adaptive-ability-tests-military-recruit-population-research-report00669nas a2200121 4500008004100000245012300041210006900164260014000233100001600373700001700389700001400406856012700420 1983 eng d00aReliability and validity of adaptive vs. conventional tests in a military recruit population (Research Rep. No. 83-1).0 aReliability and validity of adaptive vs conventional tests in a  aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aMartin, J T1 aMcBride, J R1 aWeiss, DJ uhttp://mail.iacat.org/content/reliability-and-validity-adaptive-vs-conventional-tests-military-recruit-population-research00511nas a2200097 4500008004100000245007700041210006900118260010900187100001400296856010300310 1983 eng d00aThe stratified adaptive computerized ability test (Research Report 73-3)0 astratified adaptive computerized ability test Research Report 73 aMinneapolis: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://mail.iacat.org/content/stratified-adaptive-computerized-ability-test-research-report-73-3-000521nas a2200133 4500008004100000245009100041210006900132300001200201490000700213100001000220700001800230700001600248856012300264 1982 eng d00aAutomated tailored testing using Raven’s Matrices and the Mill Hill vocabulary tests0 aAutomated tailored testing using Raven s Matrices and the Mill H a331-3440 v171 aWatts1 aBaddeley, A D1 aWilliams, M uhttp://mail.iacat.org/content/automated-tailored-testing-using-raven%E2%80%99s-matrices-and-mill-hill-vocabulary-tests00642nas a2200097 4500008004100000245008800041210006900129260022100198100001700419856010800436 1982 eng d00aComputerized testing in the German Federal Armed Forces (FAF): Empirical approaches0 aComputerized testing in the German Federal Armed Forces FAF Empi aD. J. Weiss (Ed.), Proceedings of the 1982 Item Response Theory and Computerized Adaptive Testing Conference (pp.353-359). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aWildgrube, W uhttp://mail.iacat.org/content/computerized-testing-german-federal-armed-forces-faf-empirical-approaches00423nas a2200109 4500008004500000245007100045210006900116300001200185490000600197100001400203856009600217 1982 Engldsh 00aImproving Measurement Quality and Efficiency with Adaptive Testing0 aImproving Measurement Quality and Efficiency with Adaptive Testi a473-4920 v61 aWeiss, DJ uhttp://mail.iacat.org/content/improving-measurement-quality-and-efficiency-adaptive-testing00406nas a2200097 4500008004100000245007100041210006900112100001600181700001300197856009800210 1982 eng d00aLegal and political considerations in large-scale adaptive testing0 aLegal and political considerations in largescale adaptive testin1 aWaters, B K1 aLee, G C uhttp://mail.iacat.org/content/legal-and-political-considerations-large-scale-adaptive-testing00620nas a2200121 4500008004100000245012000041210006900161260010000230100001700330700001400347700001300361856012400374 1982 eng d00aPredictive validity of conventional and adaptive tests in an Air Force training environment (Report AFHRL-TR-81-40)0 aPredictive validity of conventional and adaptive tests in an Air aBrooks Air Force Base TX: Air Force Human Resources Laboratory, Manpower and Personnel Division1 aSympson, J B1 aWeiss, DJ1 aRee, M J uhttp://mail.iacat.org/content/predictive-validity-conventional-and-adaptive-tests-air-force-training-environment-report00603nas a2200109 4500008004100000245005800041210005800099260022200157100001400379700001800393856008200411 1982 eng d00aRobustness of adaptive testing to multidimensionality0 aRobustness of adaptive testing to multidimensionality aD. J. Weiss (Ed.), Proceedings of the 1982 Item Response Theory and Computerized Adaptive Testing Conference. Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program. {PDF file, 1.1 aWeiss, DJ1 aSuhadolnik, D uhttp://mail.iacat.org/content/robustness-adaptive-testing-multidimensionality00324nas a2200109 4500008004100000245003700041210003700078300001200115490000600127100001800133856006300151 1982 eng d00aSequential testing for selection0 aSequential testing for selection a337-3510 v61 aWeitzman, R A uhttp://mail.iacat.org/content/sequential-testing-selection00330nas a2200109 4500008004500000245003700045210003700082300001200119490000600131100001800137856006500155 1982 Engldsh 00aSequential Testing for Selection0 aSequential Testing for Selection a337-3510 v61 aWeitzman, R A uhttp://mail.iacat.org/content/sequential-testing-selection-000623nas a2200097 4500008004100000245008500041210006900126260020700195100001800402856010500420 1982 eng d00aUse of Sequential Testing to Prescreen Prospective Entrants to Military Service.0 aUse of Sequential Testing to Prescreen Prospective Entrants to M aD. J. Weiss (Ed.), Proceedings of the 1982 Item Response Theory and Computerized Adaptive Testing Conference Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aWeitzman, R A uhttp://mail.iacat.org/content/use-sequential-testing-prescreen-prospective-entrants-military-service00648nas a2200109 4500008004100000245013300041210006900174260013900243100001800382700001400400856012400414 1981 eng d00aFactors influencing the psychometric characteristics of an adaptive testing strategy for test batteries (Research Rep. No. 81-4)0 aFactors influencing the psychometric characteristics of an adapt aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aMaurelli, V A1 aWeiss, DJ uhttp://mail.iacat.org/content/factors-influencing-psychometric-characteristics-adaptive-testing-strategy-test-batteries00446nas a2200097 4500008004100000245005600041210005500097260009700152100001400249856008500263 1981 eng d00aFinal report: Computerized adaptive ability testing0 aFinal report Computerized adaptive ability testing aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ uhttp://mail.iacat.org/content/final-report-computerized-adaptive-ability-testing00418nas a2200109 4500008004100000245007100041210006900112300001200181490000700193100001500200856009300215 1981 eng d00aOptimal item difficulty for the three-parameter normal ogive model0 aOptimal item difficulty for the threeparameter normal ogive mode a461-4640 v461 aWolfe, J H uhttp://mail.iacat.org/content/optimal-item-difficulty-three-parameter-normal-ogive-model00602nas a2200109 4500008004100000245010900041210006900150260011400219100001900333700001400352856012600366 1981 eng d00aA validity comparison of adaptive and conventional strategies for mastery testing (Research Report 81-3)0 avalidity comparison of adaptive and conventional strategies for  aMinneapolis, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://mail.iacat.org/content/validity-comparison-adaptive-and-conventional-strategies-mastery-testing-research-report-8100631nas a2200109 4500008004100000245014500041210006900186260011400255100001900369700001400388856011900402 1980 eng d00aAn alternate-forms reliability and concurrent validity comparison of Bayesian adaptive and conventional ability tests (Research Report 80-5)0 aalternateforms reliability and concurrent validity comparison of aMinneapolis, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://mail.iacat.org/content/alternate-forms-reliability-and-concurrent-validity-comparison-bayesian-adaptive-and00609nas a2200109 4500008004100000245012300041210006900164260011400233100001900347700001400366856011900380 1980 eng d00aA comparison of adaptive, sequential, and conventional testing strategies for mastery decisions (Research Report 80-4)0 acomparison of adaptive sequential and conventional testing strat aMinneapolis, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://mail.iacat.org/content/comparison-adaptive-sequential-and-conventional-testing-strategies-mastery-decisions00707nas a2200109 4500008004100000245009600041210006900137260024100206100001900447700001400466856011700480 1980 eng d00aA comparison of ICC-based adaptive mastery testing and the Waldian probability ratio method0 acomparison of ICCbased adaptive mastery testing and the Waldian  aD. J. Weiss (Ed.). Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 120-139). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://mail.iacat.org/content/comparison-icc-based-adaptive-mastery-testing-and-waldian-probability-ratio-method00633nas a2200097 4500008004100000245006600041210006400107260026000171100001700431856008700448 1980 eng d00aComputerized testing in the German Federal Armed Forces (FAF)0 aComputerized testing in the German Federal Armed Forces FAF aD. J. Weiss (Ed.), Proceedings of the 1979 Item Response Theory and Computerized Adaptive Testing Conference (pp. 68-77). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laborator1 aWildgrube, W uhttp://mail.iacat.org/content/computerized-testing-german-federal-armed-forces-faf00586nas a2200109 4500008004100000245008500041210006900126260013900195100001800334700001400352856011000366 1980 eng d00aCriterion-related validity of adaptive testing strategies (Research Report 80-3)0 aCriterionrelated validity of adaptive testing strategies Researc aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aThompson, J G1 aWeiss, DJ uhttp://mail.iacat.org/content/criterion-related-validity-adaptive-testing-strategies-research-report-80-300501nas a2200097 4500008004100000245002600041210002500067260024000092100001600332856005500348 1980 eng d00aDiscussion: Session 10 aDiscussion Session 1 aD. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 51-55). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aWaters, B K uhttp://mail.iacat.org/content/discussion-session-100617nas a2200133 4500008004100000245009600041210006900137260009700206100001400303700001600317700001800333700001400351856011800365 1980 eng d00aEffects of computerized adaptive testing on Black and White students (Research Report 79-2)0 aEffects of computerized adaptive testing on Black and White stud aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aPine, S M1 aChurch, A T1 aGialluca, K A1 aWeiss, DJ uhttp://mail.iacat.org/content/effects-computerized-adaptive-testing-black-and-white-students-research-report-79-200478nas a2200097 4500008004100000245006300041210006200104260010800166100001400274856009200288 1980 eng d00aFinal report: Computerized adaptive performance evaluation0 aFinal report Computerized adaptive performance evaluation aMinneapolis: Univerity of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://mail.iacat.org/content/final-report-computerized-adaptive-performance-evaluation00726nas a2200109 4500008004100000245011500041210006900156260023700225100001700462700001400479856012300493 1980 eng d00aParallel forms reliability and measurement accuracy comparison of adaptive and conventional testing strategies0 aParallel forms reliability and measurement accuracy comparison o aD. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 16-34). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aJohnson, M J1 aWeiss, DJ uhttp://mail.iacat.org/content/parallel-forms-reliability-and-measurement-accuracy-comparison-adaptive-and-conventional00492nam a2200097 4500008004100000245006900041210006900110260010900179100001400288856009200302 1980 eng d00aProceedings of the 1979 Computerized Adaptive Testing Conference0 aProceedings of the 1979 Computerized Adaptive Testing Conference aMinneapolis: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://mail.iacat.org/content/proceedings-1979-computerized-adaptive-testing-conference00527nas a2200109 4500008004100000245007800041210006900119260009700188100001900285700001400304856009900318 1979 eng d00aAn adaptive testing strategy for mastery decisions (Research Report 79-5)0 aadaptive testing strategy for mastery decisions Research Report  aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aKingsbury, G G1 aWeiss, DJ uhttp://mail.iacat.org/content/adaptive-testing-strategy-mastery-decisions-research-report-79-500598nas a2200109 4500008003900000245013000039210006900169260009700238100001800335700001400353856012100367 1979 d00aEfficiency of an adaptive inter-subtest branching strategy in the measurement of classroom achievement (Research Report 79-6)0 aEfficiency of an adaptive intersubtest branching strategy in the aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aGialluca, K A1 aWeiss, DJ uhttp://mail.iacat.org/content/efficiency-adaptive-inter-subtest-branching-strategy-measurement-classroom-achievement00569nas a2200109 4500008004100000245010400041210006900145260009700214100001400311700001400325856012000339 1978 eng d00aA comparison of the fairness of adaptive and conventional testing strategies (Research Report 78-1)0 acomparison of the fairness of adaptive and conventional testing  aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aPine, S M1 aWeiss, DJ uhttp://mail.iacat.org/content/comparison-fairness-adaptive-and-conventional-testing-strategies-research-report-78-100576nas a2200109 4500008003900000245008200039210006900121260014200190100001500332700001400347856010500361 1978 d00aA construct validation of adaptive achievement testing (Research Report 78-4)0 aconstruct validation of adaptive achievement testing Research Re aMinneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aBejar, I I1 aWeiss, DJ uhttp://mail.iacat.org/content/construct-validation-adaptive-achievement-testing-research-report-78-400492nam a2200097 4500008004100000245006900041210006900110260010900179100001400288856009200302 1978 eng d00aProceedings of the 1977 Computerized Adaptive Testing Conference0 aProceedings of the 1977 Computerized Adaptive Testing Conference aMinneapolis: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://mail.iacat.org/content/proceedings-1977-computerized-adaptive-testing-conference00473nas a2200121 4500008004100000245008900041210006900130300001200199490000600211100001400217700001400231856010600245 1978 eng d00aThe stratified adaptive ability test as a tool for personnel selection and placement0 astratified adaptive ability test as a tool for personnel selecti a135-1510 v81 aVale, C D1 aWeiss, DJ uhttp://mail.iacat.org/content/stratified-adaptive-ability-test-tool-personnel-selection-and-placement00539nas a2200109 4500008003900000245008700039210006900126260009700195100001500292700001400307856010800321 1977 d00aAn adaptive testing strategy for achievement test batteries (Research Rep No 77-6)0 aadaptive testing strategy for achievement test batteries Researc aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aBrown, J M1 aWeiss, DJ uhttp://mail.iacat.org/content/adaptive-testing-strategy-achievement-test-batteries-research-rep-no-77-600535nas a2200097 4500008004100000245007300041210006900114260014200183100001400325856009800339 1977 eng d00aApplications of computerized adaptive testing (Research Report 77-1)0 aApplications of computerized adaptive testing Research Report 77 aMinneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://mail.iacat.org/content/applications-computerized-adaptive-testing-research-report-77-100561nas a2200121 4500008004100000245009900041210006900140260007200209100001500281700001400296700001900310856011000329 1977 eng d00aCalibration of an item pool for the adaptive measurement of achievement (Research Report 77-5)0 aCalibration of an item pool for the adaptive measurement of achi aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBejar, I I1 aWeiss, DJ1 aKingsbury, G G uhttp://mail.iacat.org/content/calibration-item-pool-adaptive-measurement-achievement-research-report-77-500442nas a2200109 4500008003900000245008500039210006900124300001200193490000600205100001600211856010500227 1977 d00aAn Empirical Investigation of the Stratified Adaptive Computerized Testing Model0 aEmpirical Investigation of the Stratified Adaptive Computerized  a141-1520 v11 aWaters, B K uhttp://mail.iacat.org/content/empirical-investigation-stratified-adaptive-computerized-testing-model00606nas a2200121 4500008004100000245013200041210006900173260007200242100001500314700001400329700001800343856012300361 1977 eng d00aAn information comparison of conventional and adaptive tests in the measurement of classroom achievement (Research Report 77-7)0 ainformation comparison of conventional and adaptive tests in the aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBejar, I I1 aWeiss, DJ1 aGialluca, K A uhttp://mail.iacat.org/content/information-comparison-conventional-and-adaptive-tests-measurement-classroom-achievement00581nas a2200109 4500008003900000245006500039210006200104260018500166100001500351700001600366856008900382 1977 d00aA Low-Cost Terminal Usable for Computerized Adaptive Testing0 aLowCost Terminal Usable for Computerized Adaptive Testing aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aLamos, J P1 aWaters, B K uhttp://mail.iacat.org/content/low-cost-terminal-usable-computerized-adaptive-testing00552nas a2200109 4500008003900000245005400039210005300093260018600146100001400332700001500346856008100361 1977 d00aMulti-Content Adaptive Measurement of Achievement0 aMultiContent Adaptive Measurement of Achievement aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aWeiss, DJ1 aBrown, J M uhttp://mail.iacat.org/content/multi-content-adaptive-measurement-achievement00541nas a2200109 4500008004100000245008700041210006900128260009700197100001400294700001400308856010900322 1977 eng d00aA rapid item search procedure for Bayesian adaptive testing (Research Report 77-4)0 arapid item search procedure for Bayesian adaptive testing Resear aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aVale, C D1 aWeiss, DJ uhttp://mail.iacat.org/content/rapid-item-search-procedure-bayesian-adaptive-testing-research-report-77-400433nas a2200109 4500008004100000245008400041210006900125300000700194490001000201100001200211856010000223 1976 eng d00aAdaptive testing: A Bayesian procedure for the efficient measurement of ability0 aAdaptive testing A Bayesian procedure for the efficient measurem a360 v13(2)1 aWood, R uhttp://mail.iacat.org/content/adaptive-testing-bayesian-procedure-efficient-measurement-ability00590nas a2200097 4500008004100000245009200041210006900133260016000202100001400362856011600376 1976 eng d00aAdaptive testing research at Minnesota: Overview, recent results, and future directions0 aAdaptive testing research at Minnesota Overview recent results a aC. L. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 24-35). Washington DC: United States Civil Service Commission.1 aWeiss, DJ uhttp://mail.iacat.org/content/adaptive-testing-research-minnesota-overview-recent-results-and-future-directions00630nas a2200109 4500008004100000245011800041210006900159260013900228100001400367700001400381856012500395 1976 eng d00aEffects of immediate knowledge of results and adaptive testing on ability test performance (Research Report 76-3)0 aEffects of immediate knowledge of results and adaptive testing o aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aBetz, N E1 aWeiss, DJ uhttp://mail.iacat.org/content/effects-immediate-knowledge-results-and-adaptive-testing-ability-test-performance-research00528nas a2200097 4500008004100000245006700041210006300108260015300171100001600324856009000340 1976 eng d00aAn empirical investigation of Weiss' stradaptive testing model0 aempirical investigation of Weiss stradaptive testing model aC. L. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 54-63.). Washington DC: U. S. Civil Service Commission.1 aWaters, B K uhttp://mail.iacat.org/content/empirical-investigation-weiss-stradaptive-testing-model00460nas a2200121 4500008004100000245007800041210006900119300001200188490000600200100001600206700001400222856010200236 1976 eng d00aHardware and software evolution of an adaptive ability measurement system0 aHardware and software evolution of an adaptive ability measureme a104-1070 v81 aDeWitt, L J1 aWeiss, DJ uhttp://mail.iacat.org/content/hardware-and-software-evolution-adaptive-ability-measurement-system00621nas a2200109 4500008004100000245011200041210006900153260013900222100001400361700001400375856012200389 1976 eng d00aPsychological effects of immediate knowledge of results and adaptive ability testing (Research Report 76-4)0 aPsychological effects of immediate knowledge of results and adap aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aBetz, N E1 aWeiss, DJ uhttp://mail.iacat.org/content/psychological-effects-immediate-knowledge-results-and-adaptive-ability-testing-research00543nas a2200109 4500008004100000245009100041210006900132260008700201100001700288700001400305856011400319 1976 eng d00aSome properties of a Bayesian adaptive ability testing strategy (Research Report 76-1)0 aSome properties of a Bayesian adaptive ability testing strategy  aMinneapolis MN: Department of Psychology, Computerized Adaptive Testing Laboratory1 aMcBride, J R1 aWeiss, DJ uhttp://mail.iacat.org/content/some-properties-bayesian-adaptive-ability-testing-strategy-research-report-76-100516nas a2200109 4500008004100000245007500041210006900116260008500185100001600270700001700286856010300303 1975 eng d00aBest test design and self-tailored testing (Research Memorandum No 19)0 aBest test design and selftailored testing Research Memorandum No aChicago: University of Chicago, Department of Education, Statistical Laboratory.1 aWright, B D1 aDouglas, G A uhttp://mail.iacat.org/content/best-test-design-and-self-tailored-testing-research-memorandum-no-1900349nas a2200109 4500008004100000245004600041210004600087300000900133490000700142100001400149856007600163 1975 eng d00aComputerized adaptive ability measurement0 aComputerized adaptive ability measurement a1-180 v281 aWeiss, DJ uhttp://mail.iacat.org/content/computerized-adaptive-ability-measurement00529nas a2200097 4500008004100000245009100041210006900132260009800201100001400299856011800313 1975 eng d00aComputerized adaptive trait measurement: Problems and prospects (Research Report 75-5)0 aComputerized adaptive trait measurement Problems and prospects R aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aWeiss, DJ uhttp://mail.iacat.org/content/computerized-adaptive-trait-measurement-problems-and-prospects-research-report-75-500525nas a2200109 4500008004100000245009000041210006900131260007200200100001400272700001400286856011500300 1975 eng d00aEmpirical and simulation studies of flexilevel ability testing (Research Report 75-3)0 aEmpirical and simulation studies of flexilevel ability testing R aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBetz, N E1 aWeiss, DJ uhttp://mail.iacat.org/content/empirical-and-simulation-studies-flexilevel-ability-testing-research-report-75-300557nas a2200109 4500008004100000245009400041210006900135260009700204100001600301700001400317856011600331 1975 eng d00aAn empirical comparison of two-stage and pyramidal ability testing (Research Report 75-1)0 aempirical comparison of twostage and pyramidal ability testing R aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aLarkin, K C1 aWeiss, DJ uhttp://mail.iacat.org/content/empirical-comparison-two-stage-and-pyramidal-ability-testing-research-report-75-100522nas a2200109 4500008004100000245007700041210006900118260009700187100001400284700001400298856010000312 1975 eng d00aA simulation study of stradaptive ability testing (Research Report 75-6)0 asimulation study of stradaptive ability testing Research Report  aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aVale, C D1 aWeiss, DJ uhttp://mail.iacat.org/content/simulation-study-stradaptive-ability-testing-research-report-75-600544nas a2200109 4500008004100000245008800041210006900129260009700198100001400295700001400309856011100323 1975 eng d00aA study of computer-administered stradaptive ability testing (Research Report 75-4)0 astudy of computeradministered stradaptive ability testing Resear aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aVale, C D1 aWeiss, DJ uhttp://mail.iacat.org/content/study-computer-administered-stradaptive-ability-testing-research-report-75-400559nas a2200109 4500008004100000245008700041210006900128260011200197100001700309700001400326856010900340 1974 eng d00aA computer software system for adaptive ability measurement (Research Report 74-1)0 acomputer software system for adaptive ability measurement Resear aMinneapolis MN: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aDe Witt, J J1 aWeiss, DJ uhttp://mail.iacat.org/content/computer-software-system-adaptive-ability-measurement-research-report-74-100579nas a2200109 4500008004100000245010500041210006900146260009700215100001600312700001400328856012700342 1974 eng d00aAn empirical investigation of computer-administered pyramidal ability testing (Research Report 74-3)0 aempirical investigation of computeradministered pyramidal abilit aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aLarkin, K C1 aWeiss, DJ uhttp://mail.iacat.org/content/empirical-investigation-computer-administered-pyramidal-ability-testing-research-report-74-300530nam a2200097 4500008004100000245012200041210006900163260006100232100001600293856012300309 1974 eng d00aAn empirical investigation of the stratified adaptive computerized testing model for the measurement of human ability0 aempirical investigation of the stratified adaptive computerized  aUnpublished Ph.D. dissertation, Florida State University1 aWaters, B K uhttp://mail.iacat.org/content/empirical-investigation-stratified-adaptive-computerized-testing-model-measurement-human00586nas a2200109 4500008004100000245006900041210006900110260017300179100001700352700001400369856009300383 1974 eng d00aRecent and projected developments in ability testing by computer0 aRecent and projected developments in ability testing by computer aEarl Jones (Ed.), Symposium Proceedings: Occupational Research and the Navy–Prospectus 1980 (TR-74-14). San Diego, CA: Navy Personnel Research and Development Center.1 aMcBride, J R1 aWeiss, DJ uhttp://mail.iacat.org/content/recent-and-projected-developments-ability-testing-computer00495nas a2200109 4500008004100000245007500041210006900116260007200185100001400257700001400271856010000285 1974 eng d00aSimulation studies of two-stage ability testing (Research Report 74-4)0 aSimulation studies of twostage ability testing Research Report 7 aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBetz, N E1 aWeiss, DJ uhttp://mail.iacat.org/content/simulation-studies-two-stage-ability-testing-research-report-74-400482nas a2200097 4500008004100000245007000041210006700111260009700178100001400275856009500289 1974 eng d00aStrategies of adaptive ability measurement (Research Report 74-5)0 aStrategies of adaptive ability measurement Research Report 745 aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ uhttp://mail.iacat.org/content/strategies-adaptive-ability-measurement-research-report-74-500534nas a2200109 4500008004100000245008700041210006900128260008700197100001700284700001400301856010900315 1974 eng d00aA word knowledge item pool for adaptive ability measurement (Research Report 74-2)0 aword knowledge item pool for adaptive ability measurement Resear aMinneapolis MN: Department of Psychology, Computerized Adaptive Testing Laboratory1 aMcBride, J R1 aWeiss, DJ uhttp://mail.iacat.org/content/word-knowledge-item-pool-adaptive-ability-measurement-research-report-74-200519nas a2200109 4500008004100000245007400041210006900115260009700184100001400281700001400295856010000309 1973 eng d00aAbility measurement: Conventional or adaptive? (Research Report 73-1)0 aAbility measurement Conventional or adaptive Research Report 731 aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ1 aBetz, N E uhttp://mail.iacat.org/content/ability-measurement-conventional-or-adaptive-research-report-73-100442nas a2200109 4500008004100000245004100041210004000082260011100122100001300233700001500246856007100261 1973 eng d00aComputer-based psychological testing0 aComputerbased psychological testing aA. Elithorn and D. Jones (Eds.), Artificial and human thinking (pp. 83-93). San Francisco CA: Jossey-Bass.1 aJones, D1 aWeinman, J uhttp://mail.iacat.org/content/computer-based-psychological-testing00536nas a2200109 4500008004100000245009700041210006900138260007200207100001400279700001400293856011900307 1973 eng d00aAn empirical study of computer-administered two-stage ability testing (Research Report 73-4)0 aempirical study of computeradministered twostage ability testing aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBetz, N E1 aWeiss, DJ uhttp://mail.iacat.org/content/empirical-study-computer-administered-two-stage-ability-testing-research-report-73-400309nas a2200109 4500008004100000245003200041210003100073300001200104490000700116100001400123856006200137 1973 eng d00aResponse-contingent testing0 aResponsecontingent testing a529-5440 v431 aWood, R L uhttp://mail.iacat.org/content/response-contingent-testing00497nas a2200097 4500008004100000245007700041210006900118260009700187100001400284856010100298 1973 eng d00aThe stratified adaptive computerized ability test (Research Report 73-3)0 astratified adaptive computerized ability test Research Report 73 aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ uhttp://mail.iacat.org/content/stratified-adaptive-computerized-ability-test-research-report-73-300483nas a2200097 4500008004100000245009400041210006900135260005000204100001400254856011700268 1972 eng d00aFully adaptive sequential testing: A Bayesian procedure for efficient ability measurement0 aFully adaptive sequential testing A Bayesian procedure for effic aUnpublished manuscript, University of Chicago1 aWood, R L uhttp://mail.iacat.org/content/fully-adaptive-sequential-testing-bayesian-procedure-efficient-ability-measurement00453nas a2200121 4500008004100000245007200041210006900113300001200182490000700194100001600201700001700217856009700234 1971 eng d00aA comparison of computer-simulated conventional and branching tests0 acomparison of computersimulated conventional and branching tests a125-1360 v311 aWaters, C J1 aBayroff, A G uhttp://mail.iacat.org/content/comparison-computer-simulated-conventional-and-branching-tests00379nam a2200097 4500008004100000245004500041210004500086260006100131100001400192856007500206 1971 eng d00aComputerized adaptive sequential testing0 aComputerized adaptive sequential testing aUnpublished doctoral dissertation, University of Chicago1 aWood, R L uhttp://mail.iacat.org/content/computerized-adaptive-sequential-testing00343nas a2200109 4500008004100000245004100041210004100082300001200123490001500135100001500150856006800165 1970 eng d00aAdaptive testing of cognitive skills0 aAdaptive testing of cognitive skills a167-1680 v5 (part 1)1 aWargo, M J uhttp://mail.iacat.org/content/adaptive-testing-cognitive-skills00314nas a2200109 4500008004100000245003700041210003300078300001200111490000700123100001400130856006000144 1969 eng d00aThe efficacy of tailored testing0 aefficacy of tailored testing a219-2220 v111 aWood, R L uhttp://mail.iacat.org/content/efficacy-tailored-testing00336nas a2200085 4500008004100000245005600041210005600097100001400153856008300167 1969 eng d00aIndividualized assessment of differential abilities0 aIndividualized assessment of differential abilities1 aWeiss, DJ uhttp://mail.iacat.org/content/individualized-assessment-differential-abilities00419nas a2200097 4500008004100000245005600041210005600097260006900153100001600222856008300238 1964 eng d00aPreliminary evaluation of simulated branching tests0 aPreliminary evaluation of simulated branching tests aU.S. Army Personnel Research Office Technical Research Note 140.1 aWaters, C J uhttp://mail.iacat.org/content/preliminary-evaluation-simulated-branching-tests00487nas a2200133 4500008004000000245006900040210006500109260006300174100001200237700001500249700001500264700001600279856005800295 0 engd00aMicrocomputer network for computer­ized adaptive testing (CAT) 0 aMicrocomputer network for computer ized adaptive testing CAT bSan Diego: Navy Personnel Research and Development Center.1 aQuan, B1 aPark, T.A.1 aSandahl, G1 aWolfe, J.H. uhttps://apps.dtic.mil/dtic/tr/fulltext/u2/a140256.pdf