00460nas a2200097 4500008004900000245009300049210006900142100001700211700001600228856011800244 In Press Engldsh 00aOptimizing cognitive ability measurement with multidimensional computer adaptive testing0 aOptimizing cognitive ability measurement with multidimensional c1 aMakransky, G1 aGlas, C A W uhttp://mail.iacat.org/content/optimizing-cognitive-ability-measurement-multidimensional-computer-adaptive-testing02022nas 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/10.1177/014662161882485601840nas a2200157 4500008003900000245010800039210006900147300001200216490000700228520134100235100001501576700001601591700001301607700001701620856004501637 2018 d00aItem Selection Methods in Multidimensional Computerized Adaptive Testing With Polytomously Scored Items0 aItem Selection Methods in Multidimensional Computerized Adaptive a677-6940 v423 aMultidimensional computerized adaptive testing (MCAT) has been developed over the past decades, and most of them can only deal with dichotomously scored items. However, polytomously scored items have been broadly used in a variety of tests for their advantages of providing more information and testing complicated abilities and skills. The purpose of this study is to discuss the item selection algorithms used in MCAT with polytomously scored items (PMCAT). Several promising item selection algorithms used in MCAT are extended to PMCAT, and two new item selection methods are proposed to improve the existing selection strategies. Two simulation studies are conducted to demonstrate the feasibility of the extended and proposed methods. The simulation results show that most of the extended item selection methods for PMCAT are feasible and the new proposed item selection methods perform well. Combined with the security of the pool, when two dimensions are considered (Study 1), the proposed modified continuous entropy method (MCEM) is the ideal of all in that it gains the lowest item exposure rate and has a relatively high accuracy. As for high dimensions (Study 2), results show that mutual information (MUI) and MCEM keep relatively high estimation accuracy, and the item exposure rates decrease as the correlation increases.1 aTu, Dongbo1 aHan, Yuting1 aCai, Yan1 aGao, Xuliang uhttps://doi.org/10.1177/014662161876274800565nas a2200145 4500008003900000245008100039210006900120100002400189700002200213700001600235700001900251700002300270700002500293856010100318 2018 d00aMeasuring patient-reported outcomes adaptively: Multidimensionality matters!0 aMeasuring patientreported outcomes adaptively Multidimensionalit1 aPaap, Muirne, C. S.1 aKroeze, Karel, A.1 aGlas, C A W1 aTerwee, C., B.1 avan der Palen, Job1 aVeldkamp, Bernard, P uhttp://mail.iacat.org/measuring-patient-reported-outcomes-adaptively-multidimensionality-matters01501nas a2200133 4500008003900000245010600039210006900145300001000214490000700224520105500231100002001286700001601306856004501322 2018 d00aUsing Automatic Item Generation to Create Solutions and Rationales for Computerized Formative Testing0 aUsing Automatic Item Generation to Create Solutions and Rational a42-570 v423 aComputerized testing provides many benefits to support formative assessment. However, the advent of computerized formative testing has also raised formidable new challenges, particularly in the area of item development. Large numbers of diverse, high-quality test items are required because items are continuously administered to students. Hence, hundreds of items are needed to develop the banks necessary for computerized formative testing. One promising approach that may be used to address this test development challenge is automatic item generation. Automatic item generation is a relatively new but rapidly evolving research area where cognitive and psychometric modeling practices are used to produce items with the aid of computer technology. The purpose of this study is to describe a new method for generating both the items and the rationales required to solve the items to produce the required feedback for computerized formative testing. The method for rationale generation is demonstrated and evaluated in the medical education domain.1 aGierl, Mark, J.1 aLai, Hollis uhttps://doi.org/10.1177/014662161772678801537nas a2200181 4500008003900000245006700039210006500106300001200171490000700183520099700190100002001187700001801207700002101225700002201246700002201268700002001290856004501310 2017 d00aATS-PD: An Adaptive Testing System for Psychological Disorders0 aATSPD An Adaptive Testing System for Psychological Disorders a792-8150 v773 aThe clinical assessment of mental disorders can be a time-consuming and error-prone procedure, consisting of a sequence of diagnostic hypothesis formulation and testing aimed at restricting the set of plausible diagnoses for the patient. In this article, we propose a novel computerized system for the adaptive testing of psychological disorders. The proposed system combines a mathematical representation of psychological disorders, known as the “formal psychological assessment,” with an algorithm designed for the adaptive assessment of an individual’s knowledge. The assessment algorithm is extended and adapted to the new application domain. Testing the system on a real sample of 4,324 healthy individuals, screened for obsessive-compulsive disorder, we demonstrate the system’s ability to support clinical testing, both by identifying the correct critical areas for each individual and by reducing the number of posed questions with respect to a standard written questionnaire.1 aDonadello, Ivan1 aSpoto, Andrea1 aSambo, Francesco1 aBadaloni, Silvana1 aGranziol, Umberto1 aVidotto, Giulio uhttps://doi.org/10.1177/001316441665218803807nas a2200145 4500008004100000245008500041210006900126260005500195520326300250653002503513653001503538653001203553100002503565856007103590 2017 eng d00aFastCAT – Customizing CAT Administration Rules to Increase Response Efficiency0 aFastCAT Customizing CAT Administration Rules to Increase Respons aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

A typical pre-requisite for CAT administration is the existence of an underlying item bank completely covering the range of the trait being measured. When a bank fails to cover the full range of the trait, examinees who are close to the floor or ceiling will often never achieve a standard error cut-off and examinees will be forced to answer items increasingly less relevant to their trait level. This scenario is fairly typical for many patients responding to patient reported outcome measures (PROMS). For IACAT 2017 ABSTRACTS BOOKLET 65 example, in the assessment of physical functioning, many item banks ceiling at about the 50%ile. For most healthy patients, after a few items the only items remaining in the bank will represent decreasing ability (even though the patient has already indicated that they are at or above the mean for the population). Another example would be for a patient with no pain taking a Pain CAT. They will probably answer “Never” pain for every succeeding item out to the maximum test length. For this project we sought to reduce patient burden, while maintaining test accuracy, through the reduction of CAT length using novel stopping rules.

We studied CAT administration assessment histories for patients who were administered Patient Reported Outcomes Measurement Information System (PROMIS) CATs. In the PROMIS 1 Wave 2 Back Pain/Depression Study, CATs were administered to N=417 cases assessed across 11 PROMIS domains. Original CAT administration rules were: start with a pre-identified item of moderate difficulty; administer a minimum four items per case; stop when an estimated theta’s SE declines to < 0.3 OR a maximum 12 items are administered.

Original CAT. 12,622 CAT administrations were analyzed. CATs ranged in number of items administered from 4 to 12 items; 72.5% were 4-item CATs. The second and third most frequently occurring CATs were 5-item (n=1102; 8.7%) and 12-item CATs (n=964; 7.6%). 64,062 items total were administered, averaging 5.1 items per CAT. Customized CAT. Three new CAT stopping rules were introduced, each with potential to increase item-presentation efficiency and maintain required score precision: Stop if a case responds to the first two items administered using an “extreme” response category (towards the ceiling or floor for the in item bank, or at ); administer a minimum two items per case; stop if the change in SE estimate (previous to current item administration) is positive but < 0.01.

The three new stopping rules reduced the total number of items administered by 25,643 to 38,419 items (40.0% reduction). After four items were administered, only n=1,824 CATs (14.5%) were still in assessment mode (vs. n=3,477 (27.5%) in the original CATs). On average, cases completed 3.0 items per CAT (vs. 5.1).

Each new rule addressed specific inefficiencies in the original CAT administration process: Cases not having or possessing a low/clinically unimportant level of the assessed domain; allow the SE <0.3 stopping criterion to come into effect earlier in the CAT administration process; cases experiencing poor domain item bank measurement, (e.g., “floor,” “ceiling” cases).

10aAdministration Rules10aEfficiency10aFastCAT1 aGershon, Richard, C. uhttps://drive.google.com/open?id=1oPJV-x0p9hRmgJ7t6k-MCC1nAoBSFM1w03003nas a2200157 4500008004100000245007600041210006900117260005500186520243700241653002102678653002302699653002002722100001602742700001602758856007102774 2017 eng d00aGenerating Rationales to Support Formative Feedback in Adaptive Testing0 aGenerating Rationales to Support Formative Feedback in Adaptive  aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Computer adaptive testing offers many important benefits to support and promote life-long learning. Computers permit testing on-demand thereby allowing students to take the test at any time during instruction; items on computerized tests are scored immediately thereby providing students with instant feedback; computerized tests permit continuous administration thereby allowing students to have more choice about when they write their exams. But despite these important benefits, the advent of computer adaptive testing has also raised formidable challenges, particularly in the area of item development. Educators must have access to large numbers of diverse, high-quality test items to implement computerize adaptive testing because items are continuously administered to students. Hence, hundreds or even thousands of items are needed to develop the test item banks necessary for computer adaptive testing. Unfortunately, educational test items, as they are currently created, are time consuming and expensive to develop because each individual item is written, initially, by a content specialist and, then, reviewed, edited, and revised by groups of content specialists to ensure the items yield reliable and valid information. Hence, item development is one of the most important problems that must be solved before we can migrate to computer adaptive testing to support life-long learning because large numbers of high-quality, content-specific, test items are required.

One promising item development method that may be used to address this challenge is with automatic item generation. Automatic item generation is a relatively new but rapidly evolving research area where cognitive and psychometric modelling practices are used produce hundreds of new test items with the aid of computer technology. The purpose of our presentation is to describe a new methodology for generating both the items and the rationales required to solve each generated item in order to produce the feedback needed to support life-long learning. Our item generation methodology will first be described. To ensure our description is practical, the method will also be demonstrated using generated items from the health sciences to demonstrate how item generation can promote life-long learning for medical educators and practitioners.

 

Session Video

10aAdaptive Testing10aformative feedback10aItem generation1 aGierl, Mark1 aBulut, Okan uhttps://drive.google.com/open?id=1O5KDFtQlDLvhNoDr7X4JO4arpJkIHKUP01106nas a2200169 4500008003900000020001400039245010200053210006900155260001500224300001400239490000700253520057900260100001900839700001600858700001700874856004500891 2017 d a0146-621600aThe Information Product Methods: A Unified Approach to Dual-Purpose Computerized Adaptive Testing0 aInformation Product Methods A Unified Approach to DualPurpose Co c2018/06/01 a321 - 3240 v423 aThis article gives a brief summary of major approaches in dual-purpose computerized adaptive testing (CAT) in which the test is tailored interactively to both an examinee?s overall ability level, ?, and attribute mastery level, α. It also proposes an information product approach whose connections to the current methods are revealed. An updated comprehensive empirical study demonstrated that the information product approach not only can offer a unified framework to connect all other approaches but also can mitigate the weighting issue in the dual-information approach.1 aZheng, Chanjin1 aHe, Guanrui1 aGao, Chunlei uhttps://doi.org/10.1177/014662161773039203841nas a2200145 4500008004100000245014000041210006900181260005500250520324600305653000803551653001103559653002903570100002503599856007103624 2017 eng d00aIssues in Trait Range Coverage for Patient Reported Outcome Measure CATs - Extending the Ceiling for Above-average Physical Functioning0 aIssues in Trait Range Coverage for Patient Reported Outcome Meas aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

The use of a measure which fails to cover the upper range of functioning may produce results which can lead to serious misinterpretation. Scores produced by such a measure may fail to recognize significant improvement, or may not be able to demonstrate functioning commensurate with an important milestone. Accurate measurement of this range is critical for the assessment of physically active adults, e.g., athletes recovering from injury and active military personnel who wish to return to active service. Alternatively, a PF measure with a low ceiling might fail to differentiate patients in rehabilitation who continue to improve, but for whom their score ceilings due to the measurement used.

The assessment of physical function (PF) has greatly benefited from modern psychometric theory and resulting scales, such as the Patient-Reported Outcomes Measurement Information System (PROMIS®) PF instruments. While PROMIS PF has extended the range of function upwards relative to older “legacy” instruments, few PROMIS PF items asses high levels of function. We report here on the development of higher functioning items for the PROMIS PF bank.

An expert panel representing orthopedics, sports/military medicine, and rehabilitation reviewed existing instruments and wrote new items. After internal review, cognitive interviews were conducted with 24 individuals of average and high levels of physical function. The remaining candidate items were administered along with 50 existing PROMIS anchor items to an internet panel screened for low, average, and high levels of physical function (N = 1,600), as well as members of Boston-area gyms (N= 344). The resulting data was subjected to standard psychometric analysis, along with multiple linking methods to place the new items on the existing PF metric. The new items were added to the full PF bank for simulated computerized adaptive testing (CAT).

Item response data was collected on 54 candidate items. Items that exhibited local dependence (LD) or differential item functioning (DIF) related to gender, age, race, education, or PF status. These items were removed from consideration. Of the 50 existing PROMIS PF items, 31 were free of DIF and LD and used as anchors. The parameters for the remaining new candidate items were estimated twice: freelyestimated and linked with coefficients and fixed-anchor calibration. Both methods were comparable and had appropriate fit. The new items were added to the full PF bank for simulated CATs. The resulting CAT was able to extend the ceiling with high precision to a T-score of 68, suggesting accurate measurement for 97% of the general population.

Extending the range of items by which PF is measured will substantially improve measurement quality, applicability, and efficiency. The bank has incorporated these extension items and is available for use in research and clinics for brief CAT administration (see www.healthmeasures.net). Future research projects should focus on recovery trajectories of the measure for individuals with above average function who are recovering from injury.

Session Video

10aCAT10aIssues10aPatient Reported Outcome1 aGershon, Richard, C. uhttps://drive.google.com/open?id=1ZC02F-dIyYovEjzpeuRdoXDiXMLFRuKb02155nas a2200145 4500008004100000245005100041210005100092260005500143520166100198653002301859653002001882100001901902700001301921856007501934 2017 eng d00aItem Parameter Drifting and Online Calibration0 aItem Parameter Drifting and Online Calibration aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Item calibration is a part of the most important topics in item response theory (IRT). Since many largescale testing programs have switched from paper and pencil (P&P) testing mode to computerized adaptive testing (CAT) mode, developing methods for efficiently calibrating new items have become vital. Among many proposed item calibration processes in CAT, online calibration is the most cost-effective. This presentation introduces an online (re)calibration design to detect item parameter drift for computerized adaptive testing (CAT) in both unidimensional and multidimensional environments. Specifically, for online calibration optimal design in unidimensional computerized adaptive testing model, a two-stage design is proposed by implementing a proportional density index algorithm. For a multidimensional computerized adaptive testing model, a four-quadrant online calibration pretest item selection design with proportional density index algorithm is proposed. Comparisons were made between different online calibration item selection strategies. Results showed that under unidimensional computerized adaptive testing, the proposed modified two-stage item selection criterion with the proportional density algorithm outperformed the other existing methods in terms of item parameter calibration and item parameter drift detection, and under multidimensional computerized adaptive testing, the online (re)calibration technique with the proposed four-quadrant item selection design with proportional density index outperformed other methods.

Session Video

10aonline calibration10aParameter Drift1 aChang, Hua-Hua1 aGuo, Rui uhttp://mail.iacat.org/item-parameter-drifting-and-online-calibration-003876nas a2200193 4500008004100000245007700041210006900118260005500187520320800242653000803450653002103458653001603479100002003495700001803515700002003533700003803553700002003591856007103611 2017 eng d00aMulti-stage Testing for a Multi-disciplined End-of primary-school Test 0 aMultistage Testing for a Multidisciplined Endof primaryschool Te aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

The Dutch secondary education system consists of five levels: basic, lower, and middle vocational education, general secondary education, and pre-academic education. The individual decision for level of secondary education is based on a combination of the teacher’s judgment and an end-of-primaryschool placement test.

This placement test encompasses the measurement of reading, language, mathematics and writing; each skill consisting of one to four subdomains. The Dutch end-of-primaryschool test is currently administered in two linear 200-item paper-based versions. The two versions differ in difficulty so as to motivate both less able and more able students, and measure both groups of students precisely. The primary goal of the test is providing a placement advice for five levels of secondary education. The secondary goal is the assessment of six different fundamental reference levels defined on reading, language, and mathematics. Because of the high stakes advice of the test, the Dutch parliament has instructed to change the format to a multistage test. A major advantage of multistage testing is that the tailoring of the tests is more strongly related to the ability of the students than to the teacher’s judgment. A separate multistage test is under development for each of the three skills measured by the reference levels to increase the classification accuracy for secondary education placement and to optimally measure the performance on the reference-level-related skills.

This symposium consists of three presentations discussing the challenges in transitioning from a linear paper-based test to a computer-based multistage test within an existing curriculum and the specification of the multistage test to meet the measurement purposes. The transitioning to a multistage test has to improve both classification accuracy and measurement precision.

First, we describe the Dutch educational system and the role of the end-of-primary-school placement test within this system. Special attention will be paid to the advantages of multistage testing over both linear testing and computerized adaptive testing, and on practical implications related to the transitioning from a linear to a multistage test.

Second, we discuss routing and reporting on the new multi-stage test. Both topics have a major impact on the quality of the placement advice and the reference mastery decisions. Several methods for routing and reporting are compared.

Third, the linear test contains 200 items to cover a broad range of different skills and to obtain a precise measurement of those skills separately. Multistage testing creates opportunities to reduce the cognitive burden for the students while maintaining the same quality of placement advice and assessment of mastering of reference levels. This presentation focuses on optimal allocation of items to test modules, optimal number of stages and modules per stage and test length reduction.

Session Video 1

Session Video 2

10amst10aMultidisciplined10aproficiency1 aStraat, Hendrik1 aGroen, Maaike1 aZijlstra, Wobbe1 aKeizer-Mittelhaëuser, Marie-Anne1 aLamoré, Michel uhttps://drive.google.com/open?id=1C5ys178p_Wl9eemQuIsI56IxDTck2z8P02365nas 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_F7kzID6zCZuVXWcFDPa01415nas a2200169 4500008003900000245007000039210006900109300001400178490000700192520091000199100001901109700002101128700001601149700001201165700001401177856005401191 2015 d00aInvestigation of Response Changes in the GRE Revised General Test0 aInvestigation of Response Changes in the GRE Revised General Tes a1002-10200 v753 aResearch on examinees’ response changes on multiple-choice tests over the past 80 years has yielded some consistent findings, including that most examinees make score gains by changing answers. This study expands the research on response changes by focusing on a high-stakes admissions test—the Verbal Reasoning and Quantitative Reasoning measures of the GRE revised General Test. We analyzed data from 8,538 examinees for Quantitative and 9,140 for Verbal sections who took the GRE revised General Test in 12 countries. The analyses yielded findings consistent with prior research. In addition, as examinees’ ability increases, the benefit of response changing increases. The study yielded significant implications for both test agencies and test takers. Computer adaptive tests often do not allow the test takers to review and revise. Findings from this study confirm the benefit of such features.1 aLiu, Ou, Lydia1 aBridgeman, Brent1 aGu, Lixiong1 aXu, Jun1 aKong, Nan uhttp://epm.sagepub.com/content/75/6/1002.abstract00554nas a2200133 4500008004500000245011300045210006900158260001200227300001000239490000600249100002700255700001700282856012100299 2014 Engldsh 00aA Comparison of Multi-Stage and Linear Test Designs for Medium-Size Licensure and Certification Examinations0 aComparison of MultiStage and Linear Test Designs for MediumSize  c02-2014 a18-360 v21 aBrossman, Bradley., G.1 aGuille, R.A. uhttp://mail.iacat.org/content/comparison-multi-stage-and-linear-test-designs-medium-size-licensure-and-certification00493nas a2200121 4500008003900000245013500039210006900174300001200243490000700255100002100262700002000283856006800303 2013 d00aThe Applicability of Multidimensional Computerized Adaptive Testing for Cognitive Ability Measurement in Organizational Assessment0 aApplicability of Multidimensional Computerized Adaptive Testing  a123-1390 v131 aMakransky, Guido1 aGlas, Cees, A W uhttp://www.tandfonline.com/doi/abs/10.1080/15305058.2012.67235200573nas a2200133 4500008004500000022001400045245013400059210006900193300001200262490000700274100001700281700001600298856012500314 2013 Engldsh  a1530-505800aThe applicability of multidimensional computerized adaptive testing to cognitive ability measurement in organizational assessment0 aapplicability of multidimensional computerized adaptive testing  a123-1390 v131 aMakransky, G1 aGlas, C A W uhttp://mail.iacat.org/content/applicability-multidimensional-computerized-adaptive-testing-cognitive-ability-measurement01744nas a2200145 4500008003900000245009400039210006900133300001200202490000700214520125900221100001901480700002501499700002101524856005301545 2012 d00aBalancing Flexible Constraints and Measurement Precision in Computerized Adaptive Testing0 aBalancing Flexible Constraints and Measurement Precision in Comp a629-6480 v723 a

Managing test specifications—both multiple nonstatistical constraints and flexibly defined constraints—has become an important part of designing item selection procedures for computerized adaptive tests (CATs) in achievement testing. This study compared the effectiveness of three procedures: constrained CAT, flexible modified constrained CAT, and the weighted penalty model in balancing multiple flexible constraints and maximizing measurement precision in a fixed-length CAT. The study also addressed the effect of two different test lengths—25 items and 50 items—and of including or excluding the randomesque item exposure control procedure with the three methods, all of which were found effective in selecting items that met flexible test constraints when used in the item selection process for longer tests. When the randomesque method was included to control for item exposure, the weighted penalty model and the flexible modified constrained CAT models performed better than did the constrained CAT procedure in maintaining measurement precision. When no item exposure control method was used in the item selection process, no practical difference was found in the measurement precision of each balancing method.

1 aMoyer, Eric, L1 aGalindo, Jennifer, L1 aDodd, Barbara, G uhttp://epm.sagepub.com/content/72/4/629.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-scale00541nas 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.COM00518nas a2200109 4500008004500000245012600045210006900171100001700240700001900257700001600276856011600292 2012 Engldsh 00aImproving personality facet scores with multidimensional computerized adaptive testing: An illustration with the NEO PI-R0 aImproving personality facet scores with multidimensional compute1 aMakransky, G1 aMortensen, E L1 aGlas, C A W uhttp://mail.iacat.org/content/improving-personality-facet-scores-multidimensional-computerized-adaptive-testing01234nas a2200121 4500008004500000245007300045210006900118300001200187490000700199520079700206100001401003856009501017 2011 Engldsh 00aA Comment on Early Student Blunders on Computer-Based Adaptive Tests0 aComment on Early Student Blunders on ComputerBased Adaptive Test a165-1740 v353 a

This article refutes a recent claim that computer-based tests produce biased scores for very proficient test takers who make mistakes on one or two initial items and that they can be reduced by using a four-parameter IRT model. Because the same effect occurs with pattern scores on nonadaptive tests, the effect results from IRT scoring, not from adaptive testing. Because very proficient test takers rarely err on items of middle difficulty, the so-called bias is one of selective data analysis. Furthermore, the apparently large score penalty for one error on an otherwise perfect response pattern is shown to result from the relative stretching of the IRT scale at very high and very low proficiencies. The recommended use of a four-parameter IRT model is shown to have drawbacks.

1 aGreen, BF uhttp://mail.iacat.org/content/comment-early-student-blunders-computer-based-adaptive-tests01223nas a2200121 4500008003900000245007300039210006900112300001200181490000700193520082900200100001901029856005301048 2011 d00aA Comment on Early Student Blunders on Computer-Based Adaptive Tests0 aComment on Early Student Blunders on ComputerBased Adaptive Test a165-1740 v353 a

This article refutes a recent claim that computer-based tests produce biased scores for very proficient test takers who make mistakes on one or two initial items and that the ‘‘bias’’ can be reduced by using a four-parameter IRT model. Because the same effect occurs with pattern scores on nonadaptive tests, the effect results from IRT scoring, not from adaptive testing. Because very proficient test takers rarely err on items of middle difficulty, the so-called bias is one of selective data analysis. Furthermore, the apparently large score penalty for one error on an otherwise perfect response pattern is shown to result from the relative stretching of the IRT scale at very high and very low proficiencies. The recommended use of a four-parameter IRT model is shown to have drawbacks.

1 aGreen, Bert, F uhttp://apm.sagepub.com/content/35/2/165.abstract01007nas a2200121 4500008004500000245008100045210006900126490000700195520054900202100001600751700001100767856010700778 2011 Engldsh 00aComputer adaptive testing for small scale programs and instructional systems0 aComputer adaptive testing for small scale programs and instructi0 v123 a

This study investigates measurement decision theory (MDT) as an underlying model for computer adaptive testing when the goal is to classify examinees into one of a finite number of groups. The first analysis compares MDT with a popular item response theory model and finds little difference in terms of the percentage of correct classifications. The second analysis examines the number of examinees needed to calibrate MDT item parameters and finds accurate classifications even with calibration sample sizes as small as 100 examinees.

1 aRudner, L M1 aGuo, F uhttp://mail.iacat.org/content/computer-adaptive-testing-small-scale-programs-and-instructional-systems01961nas 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-project01696nas a2200217 4500008004100000020004600041245012100087210006900208250001500277300001100292490000700303520094700310100001701257700001301274700001601287700001001303700001201313700001601325700001801341856011901359 2011 eng d a1541-3144 (Electronic)0194-2638 (Linking)00aContent range and precision of a computer adaptive test of upper extremity function for children with cerebral palsy0 aContent range and precision of a computer adaptive test of upper a2010/10/15 a90-1020 v313 aThis article reports on the content range and measurement precision of an upper extremity (UE) computer adaptive testing (CAT) platform of physical function in children with cerebral palsy. Upper extremity items representing skills of all abilities were administered to 305 parents. These responses were compared with two traditional standardized measures: Pediatric Outcomes Data Collection Instrument and Functional Independence Measure for Children. The UE CAT correlated strongly with the upper extremity component of these measures and had greater precision when describing individual functional ability. The UE item bank has wider range with items populating the lower end of the ability spectrum. This new UE item bank and CAT have the capability to quickly assess children of all ages and abilities with good precision and, most importantly, with items that are meaningful and appropriate for their age and level of physical function.1 aMontpetit, K1 aHaley, S1 aBilodeau, N1 aNi, P1 aTian, F1 aGorton, 3rd1 aMulcahey, M J uhttp://mail.iacat.org/content/content-range-and-precision-computer-adaptive-test-upper-extremity-function-children02593nas a2200313 4500008004100000020004600041245011200087210006900199250001500268260001900283300000700302490000600309520160100315100001901916700001801935700001701953700001801970700001701988700001402005700001602019700001502035700001402050700002602064700001602090700001302106700001502119700001902134856012602153 2011 Eng d a1477-7525 (Electronic)1477-7525 (Linking)00aCross-cultural development of an item list for computer-adaptive testing of fatigue in oncological patients0 aCrosscultural development of an item list for computeradaptive t a2011/03/31 cMarch 29, 2011 a100 v93 aABSTRACT: INTRODUCTION: Within an ongoing project of the EORTC Quality of Life Group, we are developing computerized adaptive test (CAT) measures for the QLQ-C30 scales. These new CAT measures are conceptualised to reflect the same constructs as the QLQ-C30 scales. Accordingly, the Fatigue-CAT is intended to capture physical and general fatigue. METHODS: The EORTC approach to CAT development comprises four phases (literature search, operationalisation, pre-testing, and field testing). Phases I-III are described in detail in this paper. A literature search for fatigue items was performed in major medical databases. After refinement through several expert panels, the remaining items were used as the basis for adapting items and/or formulating new items fitting the EORTC item style. To obtain feedback from patients with cancer, these English items were translated into Danish, French, German, and Spanish and tested in the respective countries. RESULTS: Based on the literature search a list containing 588 items was generated. After a comprehensive item selection procedure focusing on content, redundancy, item clarity and item difficulty a list of 44 fatigue items was generated. Patient interviews (n=52) resulted in 12 revisions of wording and translations. DISCUSSION: The item list developed in phases I-III will be further investigated within a field-testing phase (IV) to examine psychometric characteristics and to fit an item response theory model. The Fatigue CAT based on this item bank will provide scores that are backward-compatible to the original QLQ-C30 fatigue scale.1 aGiesinger, J M1 aPetersen, M A1 aGroenvold, M1 aAaronson, N K1 aArraras, J I1 aConroy, T1 aGamper, E M1 aKemmler, G1 aKing, M T1 aOberguggenberger, A S1 aVelikova, G1 aYoung, T1 aHolzner, B1 aEortc-Qlg, E O uhttp://mail.iacat.org/content/cross-cultural-development-item-list-computer-adaptive-testing-fatigue-oncological-patients01889nas a2200169 4500008004500000245015100045210006900196490000700265520128400272100001601556700001701572700001401589700001501603700001501618700001401633856007201647 2011 Engldsh 00aDesign of a Computer-Adaptive Test to Measure English Literacy and Numeracy in the Singapore Workforce: Considerations, Benefits, and Implications0 aDesign of a ComputerAdaptive Test to Measure English Literacy an0 v123 a

A computer adaptive test CAT) is a delivery methodology that serves the larger goals of the assessment system in which it is embedded. A thorough analysis of the assessment system for which a CAT is being designed is critical to ensure that the delivery platform is appropriate and addresses all relevant complexities. As such, a CAT engine must be designed to conform to the
validity and reliability of the overall system. This design takes the form of adherence to the assessment goals and objectives of the adaptive assessment system. When the assessment is adapted for use in another country, consideration must be given to any necessary revisions including content differences. This article addresses these considerations while drawing, in part, on the process followed in the development of the CAT delivery system designed to test English language workplace skills for the Singapore Workforce Development Agency. Topics include item creation and selection, calibration of the item pool, analysis and testing of the psychometric properties, and reporting and interpretation of scores. The characteristics and benefits of the CAT delivery system are detailed as well as implications for testing programs considering the use of a
CAT delivery system.

1 aJacobsen, J1 aAckermann, R1 aEgüez, J1 aGanguli, D1 aRickard, P1 aTaylor, L uhttp://www.testpublishers.org/journal-of-applied-testing-technology01252nas a2200181 4500008004100000245012100041210006900162260001200231520055600243653003300799653000800832653001900840653003500859100001800894700001600912700002200928856012000950 2011 eng d00aItem Selection Methods based on Multiple Objective Approaches for Classification of Respondents into Multiple Levels0 aItem Selection Methods based on Multiple Objective Approaches fo c10/20113 a

Is it possible to develop new item selection methods which take advantage of the fact that we want to classify into multiple categories? New methods: Taking multiple points on the ability scale into account; Based on multiple objective approaches.

Conclusions

10aadaptive classification test10aCAT10aitem selection10asequential classification test1 aGroen, Maaike1 aEggen, Theo1 aVeldkamp, Bernard uhttp://mail.iacat.org/content/item-selection-methods-based-multiple-objective-approaches-classification-respondents01203nas a2200145 4500008003900000245005800039210005600097300001000153490000700163520077300170100001900943700002200962700002100984856005201005 2011 d00aA New Stopping Rule for Computerized Adaptive Testing0 aNew Stopping Rule for Computerized Adaptive Testing a37-530 v713 a

The goal of the current study was to introduce a new stopping rule for computerized adaptive testing (CAT). The predicted standard error reduction (PSER) stopping rule uses the predictive posterior variance to determine the reduction in standard error that would result from the administration of additional items. The performance of the PSER was compared with that of the minimum standard error stopping rule and a modified version of the minimum information stopping rule in a series of simulated adaptive tests, drawn from a number of item pools. Results indicate that the PSER makes efficient use of CAT item pools, administering fewer items when predictive gains in information are small and increasing measurement precision when information is abundant.

1 aChoi, Seung, W1 aGrady, Matthew, W1 aDodd, Barbara, G uhttp://epm.sagepub.com/content/71/1/37.abstract01445nas a2200133 4500008003900000245012700039210006900166300001400235490000700249520096400256100001701220700002001237856005401257 2011 d00aPolytomous Adaptive Classification Testing: Effects of Item Pool Size, Test Termination Criterion, and Number of Cutscores0 aPolytomous Adaptive Classification Testing Effects of Item Pool  a1006-10220 v713 a

Computer-adaptive classification tests focus on classifying respondents in different proficiency groups (e.g., for pass/fail decisions). To date, adaptive classification testing has been dominated by research on dichotomous response formats and classifications in two groups. This article extends this line of research to polytomous classification tests for two- and three-group scenarios (e.g., inferior, mediocre, and superior proficiencies). Results of two simulation experiments with generated and real responses (N = 2,000) to established personality scales of different length (12, 20, or 29 items) demonstrate that adaptive item presentations significantly reduce the number of items required to make such classification decisions while maintaining a consistent classification accuracy. Furthermore, the simulations highlight the importance of the selected test termination criterion, which has a significant impact on the average test length.

1 aGnambs, Timo1 aBatinic, Bernad uhttp://epm.sagepub.com/content/71/6/1006.abstract00477nas a2200121 4500008004500000245008000045210006900125300001200194490000700206100001700213700001600230856010900246 2011 Engldsh 00aUnproctored Internet test verification: Using adaptive confirmation testing0 aUnproctored Internet test verification Using adaptive confirmati a608-6300 v141 aMakransky, G1 aGlas, C A W uhttp://mail.iacat.org/content/unproctored-internet-test-verification-using-adaptive-confirmation-testing01393nas a2200145 4500008004100000245007100041210006900112260001200181520089200193653000801085653001801093653001701111100002601128856009301154 2011 eng d00aWalking the Tightrope: Using Better Content Control to Improve CAT0 aWalking the Tightrope Using Better Content Control to Improve CA c10/20113 a

All testing involves a balance between measurement precision and content considerations. CAT item-selection algorithms have evolved to accommodate content considerations. Reviews CAT evolution including: Original/”Pure” adaptive exams, Constrained CAT, Weighted-deviations method, Shadow-Test Approach, Testlets instead of fully adapted tests, Administration of one item may preclude the administration of other item(s), and item relationships.

Research Questions

 

10aCAT10aCAT evolution10atest content1 aGialluca, Kathleen, A uhttp://mail.iacat.org/content/walking-tightrope-using-better-content-control-improve-cat00412nas a2200109 4500008004100000245006400041210006400105300001200169100001600181700001300197856009200210 2010 eng d00aAdaptive Mastery Testing Using a Multidimensional IRT Model0 aAdaptive Mastery Testing Using a Multidimensional IRT Model a409-4311 aGlas, C A W1 aVos, H J uhttp://mail.iacat.org/content/adaptive-mastery-testing-using-multidimensional-irt-model00407nas a2200109 4500008004500000245006300045210006000108490000700168100001700175700001600192856008900208 2010 Engldsh 00aAn automatic online calibration design in adaptive testing0 aautomatic online calibration design in adaptive testing0 v111 aMakransky, G1 aGlas, C A W uhttp://mail.iacat.org/content/automatic-online-calibration-design-adaptive-testing-003104nas a2200445 4500008004100000020004100041245012000082210006900202250001500271260001000286300001100296490000700307520175400314653003802068653002102106653001002127653000902137653002202146653002802168653003302196653001102229653001102240653000902251653001602260653001802276653001902294653003102313653003102344653001602375100001602391700001002407700001402417700001502431700001402446700001502460700001802475700002402493700001802517856012302535 2010 eng d a0161-8105 (Print)0161-8105 (Linking)00aDevelopment and validation of patient-reported outcome measures for sleep disturbance and sleep-related impairments0 aDevelopment and validation of patientreported outcome measures f a2010/06/17 cJun 1 a781-920 v333 aSTUDY OBJECTIVES: To develop an archive of self-report questions assessing sleep disturbance and sleep-related impairments (SRI), to develop item banks from this archive, and to validate and calibrate the item banks using classic validation techniques and item response theory analyses in a sample of clinical and community participants. DESIGN: Cross-sectional self-report study. SETTING: Academic medical center and participant homes. PARTICIPANTS: One thousand nine hundred ninety-three adults recruited from an Internet polling sample and 259 adults recruited from medical, psychiatric, and sleep clinics. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: This study was part of PROMIS (Patient-Reported Outcomes Information System), a National Institutes of Health Roadmap initiative. Self-report item banks were developed through an iterative process of literature searches, collecting and sorting items, expert content review, qualitative patient research, and pilot testing. Internal consistency, convergent validity, and exploratory and confirmatory factor analysis were examined in the resulting item banks. Factor analyses identified 2 preliminary item banks, sleep disturbance and SRI. Item response theory analyses and expert content review narrowed the item banks to 27 and 16 items, respectively. Validity of the item banks was supported by moderate to high correlations with existing scales and by significant differences in sleep disturbance and SRI scores between participants with and without sleep disorders. CONCLUSIONS: The PROMIS sleep disturbance and SRI item banks have excellent measurement properties and may prove to be useful for assessing general aspects of sleep and SRI with various groups of patients and interventions.10a*Outcome Assessment (Health Care)10a*Self Disclosure10aAdult10aAged10aAged, 80 and over10aCross-Sectional Studies10aFactor Analysis, Statistical10aFemale10aHumans10aMale10aMiddle Aged10aPsychometrics10aQuestionnaires10aReproducibility of Results10aSleep Disorders/*diagnosis10aYoung Adult1 aBuysse, D J1 aYu, L1 aMoul, D E1 aGermain, A1 aStover, A1 aDodds, N E1 aJohnston, K L1 aShablesky-Cade, M A1 aPilkonis, P A uhttp://mail.iacat.org/content/development-and-validation-patient-reported-outcome-measures-sleep-disturbance-and-sleep02224nas a2200289 4500008004100000020004600041245010800087210006900195250001500264300001200279490000700291520131000298100001801608700001701626700001801643700001401661700001401675700001801689700001401707700001701721700001501738700001301753700001401766700001601780700001301796856012501809 2010 Eng d a1573-2649 (Electronic)0962-9343 (Linking)00aDevelopment of computerized adaptive testing (CAT) for the EORTC QLQ-C30 physical functioning dimension0 aDevelopment of computerized adaptive testing CAT for the EORTC Q a2010/10/26 a479-4900 v203 aPURPOSE: Computerized adaptive test (CAT) methods, based on item response theory (IRT), enable a patient-reported outcome instrument to be adapted to the individual patient while maintaining direct comparability of scores. The EORTC Quality of Life Group is developing a CAT version of the widely used EORTC QLQ-C30. We present the development and psychometric validation of the item pool for the first of the scales, physical functioning (PF). METHODS: Initial developments (including literature search and patient and expert evaluations) resulted in 56 candidate items. Responses to these items were collected from 1,176 patients with cancer from Denmark, France, Germany, Italy, Taiwan, and the United Kingdom. The items were evaluated with regard to psychometric properties. RESULTS: Evaluations showed that 31 of the items could be included in a unidimensional IRT model with acceptable fit and good content coverage, although the pool may lack items at the upper extreme (good PF). There were several findings of significant differential item functioning (DIF). However, the DIF findings appeared to have little impact on the PF estimation. CONCLUSIONS: We have established an item pool for CAT measurement of PF and believe that this CAT instrument will clearly improve the EORTC measurement of PF.1 aPetersen, M A1 aGroenvold, M1 aAaronson, N K1 aChie, W C1 aConroy, T1 aCostantini, A1 aFayers, P1 aHelbostad, J1 aHolzner, B1 aKaasa, S1 aSinger, S1 aVelikova, G1 aYoung, T uhttp://mail.iacat.org/content/development-computerized-adaptive-testing-cat-eortc-qlq-c30-physical-functioning-dimension00359nam a2200121 4500008004100000245003300041210003300074260002300107300000800130100002300138700001600161856006000177 2010 eng d00aElements of Adaptive Testing0 aElements of Adaptive Testing aNew YorkbSpringer a4371 avan der Linden, WJ1 aGlas, C A W uhttp://mail.iacat.org/content/elements-adaptive-testing00471nas a2200121 4500008004100000245007900041210006900120300001200189100001600201700002300217700001700240856009200257 2010 eng d00aEstimation of the Parameters in an Item-Cloning Model for Adaptive Testing0 aEstimation of the Parameters in an ItemCloning Model for Adaptiv a289-3141 aGlas, C A W1 avan der Linden, WJ1 aGeerlings, H uhttp://mail.iacat.org/content/estimation-parameters-item-cloning-model-adaptive-testing00353nas a2200097 4500008004100000245005200041210005200093300001200145100001600157856008200173 2010 eng d00aItem Parameter Estimation and Item Fit Analysis0 aItem Parameter Estimation and Item Fit Analysis a269-2881 aGlas, C A W uhttp://mail.iacat.org/content/item-parameter-estimation-and-item-fit-analysis00482nas 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-testing01562nas a2200157 4500008004100000020004100041245008400082210006900166250001500235300001100250490000700261520099300268100001601261700002301277856010401300 2010 eng d a0007-1102 (Print)0007-1102 (Linking)00aMarginal likelihood inference for a model for item responses and response times0 aMarginal likelihood inference for a model for item responses and a2010/01/30 a603-260 v633 a

Marginal maximum-likelihood procedures for parameter estimation and testing the fit of a hierarchical model for speed and accuracy on test items are presented. The model is a composition of two first-level models for dichotomous responses and response times along with multivariate normal models for their item and person parameters. It is shown how the item parameters can easily be estimated using Fisher's identity. To test the fit of the model, Lagrange multiplier tests of the assumptions of subpopulation invariance of the item parameters (i.e., no differential item functioning), the shape of the response functions, and three different types of conditional independence were derived. Simulation studies were used to show the feasibility of the estimation and testing procedures and to estimate the power and Type I error rate of the latter. In addition, the procedures were applied to an empirical data set from a computerized adaptive test of language comprehension.

1 aGlas, C A W1 avan der Linden, WJ uhttp://mail.iacat.org/content/marginal-likelihood-inference-model-item-responses-and-response-times01300nas a2200181 4500008004100000020004100041245005800082210005600140250001500196260001000211300000900221490000700230520075600237100001400993700001501007700001401022856008201036 2010 Eng d a0013-1644 (Print)0013-1644 (Linking)00aA new stopping rule for computerized adaptive testing0 anew stopping rule for computerized adaptive testing a2011/02/01 cDec 1 a1-170 v703 aThe goal of the current study was to introduce a new stopping rule for computerized adaptive testing. The predicted standard error reduction stopping rule (PSER) uses the predictive posterior variance to determine the reduction in standard error that would result from the administration of additional items. The performance of the PSER was compared to that of the minimum standard error stopping rule and a modified version of the minimum information stopping rule in a series of simulated adaptive tests, drawn from a number of item pools. Results indicate that the PSER makes efficient use of CAT item pools, administering fewer items when predictive gains in information are small and increasing measurement precision when information is abundant.1 aChoi, S W1 aGrady, M W1 aDodd, B G uhttp://mail.iacat.org/content/new-stopping-rule-computerized-adaptive-testing00350nas a2200109 4500008004100000245004300041210004200084300001200126100001300138700001600151856007300167 2010 eng d00aTestlet-Based Adaptive Mastery Testing0 aTestletBased Adaptive Mastery Testing a387-4091 aVos, H J1 aGlas, C A W uhttp://mail.iacat.org/content/testlet-based-adaptive-mastery-testing01858nas a2200181 4500008004100000020001400041245011000055210006900165300001200234490000700246520122300253100001601476700001601492700001601508700001201524700001301536856012701549 2010 eng d a1529-771300aThe use of PROMIS and assessment center to deliver patient-reported outcome measures in clinical research0 ause of PROMIS and assessment center to deliver patientreported o a304-3140 v113 aThe Patient-Reported Outcomes Measurement Information System (PROMIS) was developed as one of the first projects funded by the NIH Roadmap for Medical Research Initiative to re-engineer the clinical research enterprise. The primary goal of PROMIS is to build item banks and short forms that measure key health outcome domains that are manifested in a variety of chronic diseases which could be used as a "common currency" across research projects. To date, item banks, short forms and computerized adaptive tests (CAT) have been developed for 13 domains with relevance to pediatric and adult subjects. To enable easy delivery of these new instruments, PROMIS built a web-based resource (Assessment Center) for administering CATs and other self-report data, tracking item and instrument development, monitoring accrual, managing data, and storing statistical analysis results. Assessment Center can also be used to deliver custom researcher developed content, and has numerous features that support both simple and complicated accrual designs (branching, multiple arms, multiple time points, etc.). This paper provides an overview of the development of the PROMIS item banks and details Assessment Center functionality.1 aGershon, RC1 aRothrock, N1 aHanrahan, R1 aBass, M1 aCella, D uhttp://mail.iacat.org/content/use-promis-and-assessment-center-deliver-patient-reported-outcome-measures-clinical-research02758nas a2200241 4500008004100000020004600041245009400087210006900181250001500250300000800265490000600273520198300279100001502262700001602277700001402293700001302307700002002320700001902340700001702359700001302376700001402389856011302403 2010 eng d a1477-7525 (Electronic)1477-7525 (Linking)00aValidation of a computer-adaptive test to evaluate generic health-related quality of life0 aValidation of a computeradaptive test to evaluate generic health a2010/12/07 a1470 v83 aBACKGROUND: Health Related Quality of Life (HRQoL) is a relevant variable in the evaluation of health outcomes. Questionnaires based on Classical Test Theory typically require a large number of items to evaluate HRQoL. Computer Adaptive Testing (CAT) can be used to reduce tests length while maintaining and, in some cases, improving accuracy. This study aimed at validating a CAT based on Item Response Theory (IRT) for evaluation of generic HRQoL: the CAT-Health instrument. METHODS: Cross-sectional study of subjects aged over 18 attending Primary Care Centres for any reason. CAT-Health was administered along with the SF-12 Health Survey. Age, gender and a checklist of chronic conditions were also collected. CAT-Health was evaluated considering: 1) feasibility: completion time and test length; 2) content range coverage, Item Exposure Rate (IER) and test precision; and 3) construct validity: differences in the CAT-Health scores according to clinical variables and correlations between both questionnaires. RESULTS: 396 subjects answered CAT-Health and SF-12, 67.2% females, mean age (SD) 48.6 (17.7) years. 36.9% did not report any chronic condition. Median completion time for CAT-Health was 81 seconds (IQ range = 59-118) and it increased with age (p < 0.001). The median number of items administered was 8 (IQ range = 6-10). Neither ceiling nor floor effects were found for the score. None of the items in the pool had an IER of 100% and it was over 5% for 27.1% of the items. Test Information Function (TIF) peaked between levels -1 and 0 of HRQoL. Statistically significant differences were observed in the CAT-Health scores according to the number and type of conditions. CONCLUSIONS: Although domain-specific CATs exist for various areas of HRQoL, CAT-Health is one of the first IRT-based CATs designed to evaluate generic HRQoL and it has proven feasible, valid and efficient, when administered to a broad sample of individuals attending primary care settings.1 aRebollo, P1 aCastejon, I1 aCuervo, J1 aVilla, G1 aGarcia-Cueto, E1 aDiaz-Cuervo, H1 aZardain, P C1 aMuniz, J1 aAlonso, J uhttp://mail.iacat.org/content/validation-computer-adaptive-test-evaluate-generic-health-related-quality-life00637nas a2200145 4500008004100000245010000041210006900141260009700210100001300307700001300320700001300333700001400346700001700360856011400377 2009 eng d00aApplications of CAT in admissions to higher education in Israel: Twenty-two years of experience0 aApplications of CAT in admissions to higher education in Israel  aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aGafni, N1 aCohen, Y1 aRoded, K1 aBaumer, M1 aMoshinsky, A uhttp://mail.iacat.org/content/applications-cat-admissions-higher-education-israel-twenty-two-years-experience00569nas a2200121 4500008004100000245008900041210006900130260009800199100001400297700001300311700001300324856011000337 2009 eng d00aAssessing the equivalence of Internet-based vs. paper-and-pencil psychometric tests.0 aAssessing the equivalence of Internetbased vs paperandpencil psy a D. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aBaumer, M1 aRoded, K1 aGafni, N uhttp://mail.iacat.org/content/assessing-equivalence-internet-based-vs-paper-and-pencil-psychometric-tests00619nas a2200145 4500008004100000245016200041210006900203300001000272490000700282100001300289700001900302700001500321700001100336856012600347 2009 eng d00aConstraint-weighted a-stratification for computerized adaptive testing with nonstatistical constraints: Balancing measurement efficiency and exposure control0 aConstraintweighted astratification for computerized adaptive tes a35-490 v691 aCheng, Y1 aChang, Hua-Hua1 aDouglas, J1 aGuo, F uhttp://mail.iacat.org/content/constraint-weighted-stratification-computerized-adaptive-testing-nonstatistical-constraints01664nas 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-000573nas a2200109 4500008004100000245010200041210006900143260009700212100002200309700001100331856012100342 2009 eng d00aGuess what? Score differences with rapid replies versus omissions on a computerized adaptive test0 aGuess what Score differences with rapid replies versus omissions aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aTalento-Miller, E1 aGuo, F uhttp://mail.iacat.org/content/guess-what-score-differences-rapid-replies-versus-omissions-computerized-adaptive-test00579nas 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-bi00432nas a2200097 4500008004100000245005500041210005500096260009700151100001100248856007500259 2009 eng d00aQuantifying the impact of compromised items in CAT0 aQuantifying the impact of compromised items in CAT aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aGuo, F uhttp://mail.iacat.org/content/quantifying-impact-compromised-items-cat00526nas a2200121 4500008004100000245006800041210006800109260009700177100001100274700001300285700001500298856009100313 2009 eng d00aUsing automatic item generation to address item demands for CAT0 aUsing automatic item generation to address item demands for CAT aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aLai, H1 aAlves, C1 aGierl, M J uhttp://mail.iacat.org/content/using-automatic-item-generation-address-item-demands-cat01675nas a2200157 4500008004100000020001400041245010500055210006900160300001200229490000600241520109700247100001601344700002001360700001601380856012101396 2009 eng d a1939-148X00aValidation of the MMPI-2 computerized adaptive version (MMPI-2-CA) in a correctional intake facility0 aValidation of the MMPI2 computerized adaptive version MMPI2CA in a279-2920 v63 aComputerized adaptive testing in personality assessment can improve efficiency by significantly reducing the number of items administered to answer an assessment question. The time savings afforded by this technique could be of particular benefit in settings where large numbers of psychological screenings are conducted, such as correctional facilities. In the current study, item and time savings, as well as the test–retest and extratest correlations associated with an audio augmented administration of all the scales of the Minnesota Multiphasic Personality Inventory (MMPI)-2 Computerized Adaptive (MMPI-2-CA) are reported. Participants include 366 men, ages 18 to 62 years (M = 33.04, SD = 10.40), undergoing intake into a large Midwestern state correctional facility. Results of the current study indicate considerable item and corresponding time savings for the MMPI-2-CA compared to conventional administration of the test, as well as comparability in terms of test–retest and correlations with external measures. Future directions of adaptive personality testing are discussed.1 aForbey, J D1 aBen-Porath, Y S1 aGartland, D uhttp://mail.iacat.org/content/validation-mmpi-2-computerized-adaptive-version-mmpi-2-ca-correctional-intake-facility00451nas a2200133 4500008003900000245006000039210005800099300001000157490000600167100002100173700001800194700001900212856008600231 2008 d00aCAT-MD: Computerized adaptive testing on mobile devices0 aCATMD Computerized adaptive testing on mobile devices a13-200 v31 aTriantafillou, E1 aGeorgiadou, E1 aEconomides, AA uhttp://mail.iacat.org/content/cat-md-computerized-adaptive-testing-mobile-devices01436nas a2200169 4500008003900000245009000039210006900129300001000198490000800208520081300216653002901029653003601058653003001094100001501124700001201139856011501151 2008 d00aComputer Adaptive-Attribute Testing A New Approach to Cognitive Diagnostic Assessment0 aComputer AdaptiveAttribute Testing A New Approach to Cognitive D a29-390 v2163 a

The influence of interdisciplinary forces stemming from developments in cognitive science,mathematical statistics, educational
psychology, and computing science are beginning to appear in educational and psychological assessment. Computer adaptive-attribute testing (CA-AT) is one example. The concepts and procedures in CA-AT can be found at the intersection between computer adaptive testing and cognitive diagnostic assessment. CA-AT allows us to fuse the administrative benefits of computer adaptive testing with the psychological benefits of cognitive diagnostic assessment to produce an innovative psychologically-based adaptive testing approach. We describe the concepts behind CA-AT as well as illustrate how it can be used to promote formative, computer-based, classroom assessment.

10acognition and assessment10acognitive diagnostic assessment10acomputer adaptive testing1 aGierl, M J1 aZhou, J uhttp://mail.iacat.org/content/computer-adaptive-attribute-testing-new-approach-cognitive-diagnostic-assessment03042nas a2200481 4500008004100000020004600041245012200087210006900209250001500278260000800293300001200301490000700313520155700320653003201877653003101909653002201940653002001962653001001982653000901992653002202001653002802023653003302051653001102084653001102095653002502106653000902131653001602140653004602156653002202202653002402224653003002248653002902278100001502307700001402322700001502336700002402351700001802375700001102393700001602404700001002420700001502430856011502445 2008 eng d a1532-821X (Electronic)0003-9993 (Linking)00aComputerized adaptive testing for follow-up after discharge from inpatient rehabilitation: II. Participation outcomes0 aComputerized adaptive testing for followup after discharge from  a2008/01/30 cFeb a275-2830 v893 aOBJECTIVES: To measure participation outcomes with a computerized adaptive test (CAT) and compare CAT and traditional fixed-length surveys in terms of score agreement, respondent burden, discriminant validity, and responsiveness. DESIGN: Longitudinal, prospective cohort study of patients interviewed approximately 2 weeks after discharge from inpatient rehabilitation and 3 months later. SETTING: Follow-up interviews conducted in patient's home setting. PARTICIPANTS: Adults (N=94) with diagnoses of neurologic, orthopedic, or medically complex conditions. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Participation domains of mobility, domestic life, and community, social, & civic life, measured using a CAT version of the Participation Measure for Postacute Care (PM-PAC-CAT) and a 53-item fixed-length survey (PM-PAC-53). RESULTS: The PM-PAC-CAT showed substantial agreement with PM-PAC-53 scores (intraclass correlation coefficient, model 3,1, .71-.81). On average, the PM-PAC-CAT was completed in 42% of the time and with only 48% of the items as compared with the PM-PAC-53. Both formats discriminated across functional severity groups. The PM-PAC-CAT had modest reductions in sensitivity and responsiveness to patient-reported change over a 3-month interval as compared with the PM-PAC-53. CONCLUSIONS: Although continued evaluation is warranted, accurate estimates of participation status and responsiveness to change for group-level analyses can be obtained from CAT administrations, with a sizeable reduction in respondent burden.10a*Activities of Daily Living10a*Adaptation, Physiological10a*Computer Systems10a*Questionnaires10aAdult10aAged10aAged, 80 and over10aChi-Square Distribution10aFactor Analysis, Statistical10aFemale10aHumans10aLongitudinal Studies10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods10aPatient Discharge10aProspective Studies10aRehabilitation/*standards10aSubacute Care/*standards1 aHaley, S M1 aGandek, B1 aSiebens, H1 aBlack-Schaffer, R M1 aSinclair, S J1 aTao, W1 aCoster, W J1 aNi, P1 aJette, A M uhttp://mail.iacat.org/content/computerized-adaptive-testing-follow-after-discharge-inpatient-rehabilitation-ii00484nam a2200097 4500008004100000245008500041210006900126260007700195100001500272856009900287 2008 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 aUnpublished Ph.D. dissertation, University of Minnesota, Minneapolis MN.1 aGuyer, R D uhttp://mail.iacat.org/content/effect-early-misfit-computerized-adaptive-testing-recovery-theta03158nas 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-assessment00424nas a2200097 4500008004100000245004900041210004600090260009700136100001100233856008200244 2007 eng d00aCAT Security: A practitioner’s perspective0 aCAT Security A practitioner s perspective aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aGuo, F uhttp://mail.iacat.org/content/cat-security-practitioner%E2%80%99s-perspective00474nas 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-model00609nas a2200121 4500008004100000245012500041210006900166260009700235100001200332700001500344700001100359856011700370 2007 eng d00aComputerized attribute-adaptive testing: A new computerized adaptive testing approach incorporating cognitive psychology0 aComputerized attributeadaptive testing A new computerized adapti aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aZhou, J1 aGierl, M J1 aCui, Y uhttp://mail.iacat.org/content/computerized-attribute-adaptive-testing-new-computerized-adaptive-testing-approach00474nas a2200121 4500008003900000245008000039210006900119490000800188100002100196700001800217700001900235856009800254 2007 d00aThe design and evaluation of a computerized adaptive test on mobile devices0 adesign and evaluation of a computerized adaptive test on mobile 0 v49.1 aTriantafillou, E1 aGeorgiadou, E1 aEconomides, AA uhttp://mail.iacat.org/content/design-and-evaluation-computerized-adaptive-test-mobile-devices00568nas a2200109 4500008004100000245010200041210006900143260009600212100001000308700001700318856012300335 2007 eng d00aDesigning optimal item pools for computerized adaptive tests with Sympson-Hetter exposure control0 aDesigning optimal item pools for computerized adaptive tests wit aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing1 aGu, L1 aReckase, M D uhttp://mail.iacat.org/content/designing-optimal-item-pools-computerized-adaptive-tests-sympson-hetter-exposure-control02894nas a2200169 4500008004100000020001400041245011300055210006900168300001200237490000700249520229000256100001302546700001602559700001302575700001402588856012202602 2007 eng d a0962-934300aThe future of outcomes measurement: item banking, tailored short-forms, and computerized adaptive assessment0 afuture of outcomes measurement item banking tailored shortforms  a133-1410 v163 aThe use of item banks and computerized adaptive testing (CAT) begins with clear definitions of important outcomes, and references those definitions to specific questions gathered into large and well-studied pools, or “banks” of items. Items can be selected from the bank to form customized short scales, or can be administered in a sequence and length determined by a computer programmed for precision and clinical relevance. Although far from perfect, such item banks can form a common definition and understanding of human symptoms and functional problems such as fatigue, pain, depression, mobility, social function, sensory function, and many other health concepts that we can only measure by asking people directly. The support of the National Institutes of Health (NIH), as witnessed by its cooperative agreement with measurement experts through the NIH Roadmap Initiative known as PROMIS (www.nihpromis.org), is a big step in that direction. Our approach to item banking and CAT is practical; as focused on application as it is on science or theory. From a practical perspective, we frequently must decide whether to re-write and retest an item, add more items to fill gaps (often at the ceiling of the measure), re-test a bank after some modifications, or split up a bank into units that are more unidimensional, yet less clinically relevant or complete. These decisions are not easy, and yet they are rarely unforgiving. We encourage people to build practical tools that are capable of producing multiple short form measures and CAT administrations from common banks, and to further our understanding of these banks with various clinical populations and ages, so that with time the scores that emerge from these many activities begin to have not only a common metric and range, but a shared meaning and understanding across users. In this paper, we provide an overview of item banking and CAT, discuss our approach to item banking and its byproducts, describe testing options, discuss an example of CAT for fatigue, and discuss models for long term sustainability of an entity such as PROMIS. Some barriers to success include limitations in the methods themselves, controversies and disagreements across approaches, and end-user reluctance to move away from the familiar. 1 aCella, D1 aGershon, RC1 aLai, J-S1 aChoi, S W uhttp://mail.iacat.org/content/future-outcomes-measurement-item-banking-tailored-short-forms-and-computerized-adaptive03105nas a2200445 4500008004100000020002200041245007100063210006900134250001500203300001200218490000700230520183100237653003802068653001902106653002102125653002002146653001402166653001102180653003002191653001102221653000902232653002502241653004602266653001802312653002602330100001302356700001402369700001702383700001302400700001502413700001502428700001702443700001402460700001802474700002302492700001602515700001602531700001502547856009702562 2007 eng d a0962-9343 (Print)00aIRT health outcomes data analysis project: an overview and summary0 aIRT health outcomes data analysis project an overview and summar a2007/03/14 a121-1320 v163 aBACKGROUND: In June 2004, the National Cancer Institute and the Drug Information Association co-sponsored the conference, "Improving the Measurement of Health Outcomes through the Applications of Item Response Theory (IRT) Modeling: Exploration of Item Banks and Computer-Adaptive Assessment." A component of the conference was presentation of a psychometric and content analysis of a secondary dataset. OBJECTIVES: A thorough psychometric and content analysis was conducted of two primary domains within a cancer health-related quality of life (HRQOL) dataset. RESEARCH DESIGN: HRQOL scales were evaluated using factor analysis for categorical data, IRT modeling, and differential item functioning analyses. In addition, computerized adaptive administration of HRQOL item banks was simulated, and various IRT models were applied and compared. SUBJECTS: The original data were collected as part of the NCI-funded Quality of Life Evaluation in Oncology (Q-Score) Project. A total of 1,714 patients with cancer or HIV/AIDS were recruited from 5 clinical sites. MEASURES: Items from 4 HRQOL instruments were evaluated: Cancer Rehabilitation Evaluation System-Short Form, European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, Functional Assessment of Cancer Therapy and Medical Outcomes Study Short-Form Health Survey. RESULTS AND CONCLUSIONS: Four lessons learned from the project are discussed: the importance of good developmental item banks, the ambiguity of model fit results, the limits of our knowledge regarding the practical implications of model misfit, and the importance in the measurement of HRQOL of construct definition. With respect to these lessons, areas for future research are suggested. The feasibility of developing item banks for broad definitions of health is discussed.10a*Data Interpretation, Statistical10a*Health Status10a*Quality of Life10a*Questionnaires10a*Software10aFemale10aHIV Infections/psychology10aHumans10aMale10aNeoplasms/psychology10aOutcome Assessment (Health Care)/*methods10aPsychometrics10aStress, Psychological1 aCook, KF1 aTeal, C R1 aBjorner, J B1 aCella, D1 aChang, C-H1 aCrane, P K1 aGibbons, L E1 aHays, R D1 aMcHorney, C A1 aOcepek-Welikson, K1 aRaczek, A E1 aTeresi, J A1 aReeve, B B uhttp://mail.iacat.org/content/irt-health-outcomes-data-analysis-project-overview-and-summary00656nas a2200121 4500008004100000245015200041210006900193260009700262100001700359700001700376700001400393856012700407 2007 eng d00aPatient-reported outcomes measurement and computerized adaptive testing: An application of post-hoc simulation to a diagnostic screening instrument0 aPatientreported outcomes measurement and computerized adaptive t aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aImmekus, J C1 aGibbons, R D1 aRush, J A uhttp://mail.iacat.org/content/patient-reported-outcomes-measurement-and-computerized-adaptive-testing-application-post-hoc01228nas a2200229 4500008004100000245014700041210006900188300001100257490000700268520046800275100001300743700001300756700001600769700001600785700001300801700001300814700001200827700001500839700001300854700001200867856011900879 2007 eng d00aThe Patient-Reported Outcomes Measurement Information System (PROMIS): progress of an NIH Roadmap cooperative group during its first two years0 aPatientReported Outcomes Measurement Information System PROMIS p aS3-S110 v453 aThe National Institutes of Health (NIH) Patient-Reported Outcomes Measurement Information System (PROMIS) Roadmap initiative (www.nihpromis.org) is a 5-year cooperative group program of research designed to develop, validate, and standardize item banks to measure patient-reported outcomes (PROs) relevant across common medical conditions. In this article, we will summarize the organization and scientific activity of the PROMIS network during its first 2 years.1 aCella, D1 aYount, S1 aRothrock, N1 aGershon, RC1 aCook, KF1 aReeve, B1 aAder, D1 aFries, J F1 aBruce, B1 aRose, M uhttp://mail.iacat.org/content/patient-reported-outcomes-measurement-information-system-promis-progress-nih-roadmap02745nas 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-patient01803nas a2200133 4500008004100000245011100041210006900152490001000221520125600231100001801487700002101505700001901526856012401545 2007 eng d00aA review of item exposure control strategies for computerized adaptive testing developed from 1983 to 20050 areview of item exposure control strategies for computerized adap0 v 5(8)3 aSince researchers acknowledged the several advantages of computerized adaptive testing (CAT) over traditional linear test administration, the issue of item exposure control has received increased attention. Due to CAT’s underlying philosophy, particular items in the item pool may be presented too often and become overexposed, while other items are rarely selected by the CAT algorithm and thus become underexposed. Several item exposure control strategies have been presented in the literature aiming to prevent overexposure of some items and to increase the use rate of rarely or never selected items. This paper reviews such strategies that appeared in the relevant literature from 1983 to 2005. The focus of this paper is on studies that have been conducted in order to evaluate the effectiveness of item exposure control strategies for dichotomous scoring, polytomous scoring and testlet-based CAT systems. In addition, the paper discusses the strengths and weaknesses of each strategy group using examples from simulation studies. No new research is presented but rather a compendium of models is reviewed with an overall objective of providing researchers of this field, especially newcomers, a wide view of item exposure control strategies.1 aGeorgiadou, E1 aTriantafillou, E1 aEconomides, AA uhttp://mail.iacat.org/content/review-item-exposure-control-strategies-computerized-adaptive-testing-developed-1983-200500475nas a2200109 4500008004100000245004400041210004400085260012600129100002300255700001600278856007100294 2007 eng d00aStatistical aspects of adaptive testing0 aStatistical aspects of adaptive testing aC. R. Rao and S. Sinharay (Eds.), Handbook of statistics (Vol. 27: Psychometrics) (pp. 801838). Amsterdam: North-Holland.1 avan der Linden, WJ1 aGlas, C A W uhttp://mail.iacat.org/content/statistical-aspects-adaptive-testing03330nas a2200469 4500008004100000020002200041245011600063210006900179250001500248260000800263300001200271490000700283520189400290653003202184653003102216653002202247653002002269653001002289653000902299653002202308653002802330653003302358653001102391653001102402653002502413653000902438653001602447653004602463653002202509653002402531653003002555653002902585100001502614700001502629700001602644700001102660700002402671700001402695700001802709700001002727856012302737 2006 eng d a0003-9993 (Print)00aComputerized adaptive testing for follow-up after discharge from inpatient rehabilitation: I. Activity outcomes0 aComputerized adaptive testing for followup after discharge from  a2006/08/01 cAug a1033-420 v873 aOBJECTIVE: To examine score agreement, precision, validity, efficiency, and responsiveness of a computerized adaptive testing (CAT) version of the Activity Measure for Post-Acute Care (AM-PAC-CAT) in a prospective, 3-month follow-up sample of inpatient rehabilitation patients recently discharged home. DESIGN: Longitudinal, prospective 1-group cohort study of patients followed approximately 2 weeks after hospital discharge and then 3 months after the initial home visit. SETTING: Follow-up visits conducted in patients' home setting. PARTICIPANTS: Ninety-four adults who were recently discharged from inpatient rehabilitation, with diagnoses of neurologic, orthopedic, and medically complex conditions. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Summary scores from AM-PAC-CAT, including 3 activity domains of movement and physical, personal care and instrumental, and applied cognition were compared with scores from a traditional fixed-length version of the AM-PAC with 66 items (AM-PAC-66). RESULTS: AM-PAC-CAT scores were in good agreement (intraclass correlation coefficient model 3,1 range, .77-.86) with scores from the AM-PAC-66. On average, the CAT programs required 43% of the time and 33% of the items compared with the AM-PAC-66. Both formats discriminated across functional severity groups. The standardized response mean (SRM) was greater for the movement and physical fixed form than the CAT; the effect size and SRM of the 2 other AM-PAC domains showed similar sensitivity between CAT and fixed formats. Using patients' own report as an anchor-based measure of change, the CAT and fixed length formats were comparable in responsiveness to patient-reported change over a 3-month interval. CONCLUSIONS: Accurate estimates for functional activity group-level changes can be obtained from CAT administrations, with a considerable reduction in administration time.10a*Activities of Daily Living10a*Adaptation, Physiological10a*Computer Systems10a*Questionnaires10aAdult10aAged10aAged, 80 and over10aChi-Square Distribution10aFactor Analysis, Statistical10aFemale10aHumans10aLongitudinal Studies10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods10aPatient Discharge10aProspective Studies10aRehabilitation/*standards10aSubacute Care/*standards1 aHaley, S M1 aSiebens, H1 aCoster, W J1 aTao, W1 aBlack-Schaffer, R M1 aGandek, B1 aSinclair, S J1 aNi, P uhttp://mail.iacat.org/content/computerized-adaptive-testing-follow-after-discharge-inpatient-rehabilitation-i-activity01613nas a2200145 4500008003900000245011900039210006900158300001200227490000700239520110300246100002001349700002001369700002501389856005301414 2006 d00aEffects of Estimation Bias on Multiple-Category Classification With an IRT-Based Adaptive Classification Procedure0 aEffects of Estimation Bias on MultipleCategory Classification Wi a545-5640 v663 a

The effects of five ability estimators, that is, maximum likelihood estimator, weighted likelihood estimator, maximum a posteriori, expected a posteriori, and Owen's sequential estimator, on the performances of the item response theory–based adaptive classification procedure on multiple categories were studied via simulations. The following results were found. (a) The Bayesian estimators were more likely to misclassify examinees into an inward category because of their inward biases, when a fixed start value of zero was assigned to every examinee. (b) When moderately accurate start values were available, however, Bayesian estimators produced classifications that were slightly more accurate than was the maximum likelihood estimator or weighted likelihood estimator. Expected a posteriori was the procedure that produced the most accurate results among the three Bayesian methods. (c) All five estimators produced equivalent efficiencies in terms of number of items required, which was 50 or more items except for abilities that were less than -2.00 or greater than 2.00.

1 aYang, Xiangdong1 aPoggio, John, C1 aGlasnapp, Douglas, R uhttp://epm.sagepub.com/content/66/4/545.abstract00451nas a2200133 4500008004100000245005600041210005600097300001200153490001200165100001800177700002100195700001900216856008200235 2006 eng d00aEvaluation parameters for computer adaptive testing0 aEvaluation parameters for computer adaptive testing a261-2780 vVol. 371 aGeorgiadou, E1 aTriantafillou, E1 aEconomides, AA uhttp://mail.iacat.org/content/evaluation-parameters-computer-adaptive-testing02187nas a2200181 4500008004100000245009900041210006900140260000800209300001400217490000700231520157400238100001401812700001301826700001401839700001601853700001301869856012301882 2006 eng d00aItem banks and their potential applications to health status assessment in diverse populations0 aItem banks and their potential applications to health status ass cNov aS189-S1970 v443 aIn the context of an ethnically diverse, aging society, attention is increasingly turning to health-related quality of life measurement to evaluate healthcare and treatment options for chronic diseases. When evaluating and treating symptoms and concerns such as fatigue, pain, or physical function, reliable and accurate assessment is a priority. Modern psychometric methods have enabled us to move from long, static tests that provide inefficient and often inaccurate assessment of individual patients, to computerized adaptive tests (CATs) that can precisely measure individuals on health domains of interest. These modern methods, collectively referred to as item response theory (IRT), can produce calibrated "item banks" from larger pools of questions. From these banks, CATs can be conducted on individuals to produce their scores on selected domains. Item banks allow for comparison of patients across different question sets because the patient's score is expressed on a common scale. Other advantages of using item banks include flexibility in terms of the degree of precision desired; interval measurement properties under most circumstances; realistic capability for accurate individual assessment over time (using CAT); and measurement equivalence across different patient populations. This work summarizes the process used in the creation and evaluation of item banks and reviews their potential contributions and limitations regarding outcome assessment and patient care, particularly when they are applied across people of different cultural backgrounds.1 aHahn, E A1 aCella, D1 aBode, R K1 aGershon, RC1 aLai, J S uhttp://mail.iacat.org/content/item-banks-and-their-potential-applications-health-status-assessment-diverse-populations02406nas a2200337 4500008004100000020002200041245010800063210006900171250001500240260000800255300001100263490000700274520139300281653002101674653002101695653001001716653001101726653001801737653001101755653000901766653001601775653003001791653002801821100001801849700001701867700001801884700001401902700001701916700001701933856011801950 2006 eng d a0962-9343 (Print)00aMultidimensional computerized adaptive testing of the EORTC QLQ-C30: basic developments and evaluations0 aMultidimensional computerized adaptive testing of the EORTC QLQC a2006/03/21 cApr a315-290 v153 aOBJECTIVE: Self-report questionnaires are widely used to measure health-related quality of life (HRQOL). Ideally, such questionnaires should be adapted to the individual patient and at the same time scores should be directly comparable across patients. This may be achieved using computerized adaptive testing (CAT). Usually, CAT is carried out for a single domain at a time. However, many HRQOL domains are highly correlated. Multidimensional CAT may utilize these correlations to improve measurement efficiency. We investigated the possible advantages and difficulties of multidimensional CAT. STUDY DESIGN AND SETTING: We evaluated multidimensional CAT of three scales from the EORTC QLQ-C30: the physical functioning, emotional functioning, and fatigue scales. Analyses utilised a database with 2958 European cancer patients. RESULTS: It was possible to obtain scores for the three domains with five to seven items administered using multidimensional CAT that were very close to the scores obtained using all 12 items and with no or little loss of measurement precision. CONCLUSION: The findings suggest that multidimensional CAT may significantly improve measurement precision and efficiency and encourage further research into multidimensional CAT. Particularly, the estimation of the model underlying the multidimensional CAT and the conceptual aspects need further investigations.10a*Quality of Life10a*Self Disclosure10aAdult10aFemale10aHealth Status10aHumans10aMale10aMiddle Aged10aQuestionnaires/*standards10aUser-Computer Interface1 aPetersen, M A1 aGroenvold, M1 aAaronson, N K1 aFayers, P1 aSprangers, M1 aBjorner, J B uhttp://mail.iacat.org/content/multidimensional-computerized-adaptive-testing-eortc-qlq-c30-basic-developments-and01470nas a2200217 4500008004100000245015400041210006900195260004600264300001200310520063100322653003000953653001100983653002500994653001601019653002201035653002301057100001801080700001501098700001401113856012501127 2005 eng d00aApplications of item response theory to improve health outcomes assessment: Developing item banks, linking instruments, and computer-adaptive testing0 aApplications of item response theory to improve health outcomes  aCambridge, UKbCambridge University Press a445-4643 a(From the chapter) The current chapter builds on Reise's introduction to the basic concepts, assumptions, popular models, and important features of IRT and discusses the applications of item response theory (IRT) modeling to health outcomes assessment. In particular, we highlight the critical role of IRT modeling in: developing an instrument to match a study's population; linking two or more instruments measuring similar constructs on a common metric; and creating item banks that provide the foundation for tailored short-form instruments or for computerized adaptive assessments. (PsycINFO Database Record (c) 2005 APA )10aComputer Assisted Testing10aHealth10aItem Response Theory10aMeasurement10aTest Construction10aTreatment Outcomes1 aHambleton, RK1 aGotay, C C1 aSnyder, C uhttp://mail.iacat.org/content/applications-item-response-theory-improve-health-outcomes-assessment-developing-item-banks01374nas a2200193 4500008004100000245005000041210004700091300001000138490000600148520081200154653001700966653002100983653002601004653002501030100001501055700001401070700002301084856007301107 2005 eng d00aAn Authoring Environment for Adaptive Testing0 aAuthoring Environment for Adaptive Testing a66-760 v83 a

SIETTE is a web-based adaptive testing system. It implements Computerized Adaptive Tests. These tests are tailor-made, theory-based tests, where questions shown to students, finalization of the test, and student knowledge estimation is accomplished adaptively. To construct these tests, SIETTE has an authoring environment comprising a suite of tools that helps teachers create questions and tests properly, and analyze students’ performance after taking a test. In this paper, we present this authoring environment in the
framework of adaptive testing. As will be shown, this set of visual tools, that contain some adaptable eatures, can be useful for teachers lacking skills in this kind of testing. Additionally, other systems that implement adaptive testing will be studied. 

10aAdaptability10aAdaptive Testing10aAuthoring environment10aItem Response Theory1 aGuzmán, E1 aConejo, R1 aGarcía-Hervás, E uhttp://mail.iacat.org/content/authoring-environment-adaptive-testing00306nas a2200109 4500008004100000245003000041210003000071300001100101490000600112100001600118856006200134 2005 eng d00aComputer adaptive testing0 aComputer adaptive testing a109-270 v61 aGershon, RC uhttp://mail.iacat.org/content/computer-adaptive-testing-001606nas a2200253 4500008004100000020002200041245003000063210003000093250001500123300001100138490000600149520095200155653001401107653002501121653002901146653001801175653001901193653001101212653001401223653001901237653002001256100001601276856006001292 2005 eng d a1529-7713 (Print)00aComputer adaptive testing0 aComputer adaptive testing a2005/02/11 a109-270 v63 aThe creation of item response theory (IRT) and Rasch models, inexpensive accessibility to high speed desktop computers, and the growth of the Internet, has led to the creation and growth of computerized adaptive testing or CAT. This form of assessment is applicable for both high stakes tests such as certification or licensure exams, as well as health related quality of life surveys. This article discusses the historical background of CAT including its many advantages over conventional (typically paper and pencil) alternatives. The process of CAT is then described including descriptions of the specific differences of using CAT based upon 1-, 2- and 3-parameter IRT and various Rasch models. Numerous specific topics describing CAT in practice are described including: initial item selection, content balancing, test difficulty, test length and stopping rules. The article concludes with the author's reflections regarding the future of CAT.10a*Internet10a*Models, Statistical10a*User-Computer Interface10aCertification10aHealth Surveys10aHumans10aLicensure10aMicrocomputers10aQuality of Life1 aGershon, RC uhttp://mail.iacat.org/content/computer-adaptive-testing00542nas a2200121 4500008004100000020001400041245014400055210006900199300001200268490000700280100001500287856011800302 2005 eng d a0146-621600aComputerized adaptive testing with the partial credit model: Estimation procedures, population distributions, and item pool characteristics0 aComputerized adaptive testing with the partial credit model Esti a433-4560 v291 aGorin, J S uhttp://mail.iacat.org/content/computerized-adaptive-testing-partial-credit-model-estimation-procedures-population01564nas a2200157 4500008003900000245014400039210006900183300001200252490000700264520099200271100002101263700002101284700002701305700002101332856005301353 2005 d00aComputerized Adaptive Testing With the Partial Credit Model: Estimation Procedures, Population Distributions, and Item Pool Characteristics0 aComputerized Adaptive Testing With the Partial Credit Model Esti a433-4560 v293 a

The primary purpose of this research is to examine the impact of estimation methods, actual latent trait distributions, and item pool characteristics on the performance of a simulated computerized adaptive testing (CAT) system. In this study, three estimation procedures are compared for accuracy of estimation: maximum likelihood estimation (MLE), expected a priori (EAP), and Warm's weighted likelihood estimation (WLE). Some research has shown that MLE and EAP perform equally well under certain conditions in polytomous CAT systems, such that they match the actual latent trait distribution. However, little research has compared these methods when prior estimates of. distributions are extremely poor. In general, it appears that MLE, EAP, and WLE procedures perform equally well when using an optimal item pool. However, the use of EAP procedures may be advantageous under nonoptimal testing conditions when the item pool is not appropriately matched to the examinees.

1 aGorin, Joanna, S1 aDodd, Barbara, G1 aFitzpatrick, Steven, J1 aShieh, Yann Yann uhttp://apm.sagepub.com/content/29/6/433.abstract00602nas a2200145 4500008004100000245014400041210006900185300001200254490000700266100001300273700001400286700002100300700001500321856012000336 2005 eng d00aComputerized adaptive testing with the partial credit model: Estimation procedures, population distributions, and item pool characteristics0 aComputerized adaptive testing with the partial credit model Esti a533-5460 v291 aGorin, J1 aDodd, B G1 aFitzpatrick, S J1 aShieh, Y Y uhttp://mail.iacat.org/content/computerized-adaptive-testing-partial-credit-model-estimation-procedures-population-000628nas a2200109 4500008004100000245009500041210006900136260016800205100001800373700001900391856010800410 2005 eng d00aThe development of the adaptive item language assessment (AILA) for mixed-ability students0 adevelopment of the adaptive item language assessment AILA for mi aProceedings E-Learn 2005 World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, 643-650, Vancouver, Canada, AACE, October 2005.1 aGiouroglou, H1 aEconomides, AA uhttp://mail.iacat.org/content/development-adaptive-item-language-assessment-aila-mixed-ability-students00650nas a2200109 4500008004100000245010000041210006900141260017200210100001800382700001900400856012100419 2005 eng d00aAn implemented theoretical framework for a common European foreign language adaptive assessment0 aimplemented theoretical framework for a common European foreign  aProceedings ICODL 2005, 3rd ternational Conference on Open and Distance Learning 'Applications of Pedagogy and Technology',339-350,Greek Open University, Patra, Greece1 aGiouroglou, H1 aEconomides, AA uhttp://mail.iacat.org/content/implemented-theoretical-framework-common-european-foreign-language-adaptive-assessment02444nas a2200373 4500008004100000020004100041245008200082210006900164250001500233260000800248300001000256490000700266520136700273653001001640653000901650653002201659653003301681653003301714653001101747653001101758653000901769653001601778653004001794653001801834653001901852100001301871700001301884700001401897700001201911700001701923700001601940700001501956856009901971 2005 eng d a0895-4356 (Print)0895-4356 (Linking)00aAn item bank was created to improve the measurement of cancer-related fatigue0 aitem bank was created to improve the measurement of cancerrelate a2005/02/01 cFeb a190-70 v583 aOBJECTIVE: Cancer-related fatigue (CRF) is one of the most common unrelieved symptoms experienced by patients. CRF is underrecognized and undertreated due to a lack of clinically sensitive instruments that integrate easily into clinics. Modern computerized adaptive testing (CAT) can overcome these obstacles by enabling precise assessment of fatigue without requiring the administration of a large number of questions. A working item bank is essential for development of a CAT platform. The present report describes the building of an operational item bank for use in clinical settings with the ultimate goal of improving CRF identification and treatment. STUDY DESIGN AND SETTING: The sample included 301 cancer patients. Psychometric properties of items were examined by using Rasch analysis, an Item Response Theory (IRT) model. RESULTS AND CONCLUSION: The final bank includes 72 items. These 72 unidimensional items explained 57.5% of the variance, based on factor analysis results. Excellent internal consistency (alpha=0.99) and acceptable item-total correlation were found (range: 0.51-0.85). The 72 items covered a reasonable range of the fatigue continuum. No significant ceiling effects, floor effects, or gaps were found. A sample short form was created for demonstration purposes. The resulting bank is amenable to the development of a CAT platform.10aAdult10aAged10aAged, 80 and over10aFactor Analysis, Statistical10aFatigue/*etiology/psychology10aFemale10aHumans10aMale10aMiddle Aged10aNeoplasms/*complications/psychology10aPsychometrics10aQuestionnaires1 aLai, J-S1 aCella, D1 aDineen, K1 aBode, R1 aVon Roenn, J1 aGershon, RC1 aShevrin, D uhttp://mail.iacat.org/content/item-bank-was-created-improve-measurement-cancer-related-fatigue00560nas 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-measurement00431nas a2200097 4500008004100000245004600041210004200087260011900129100001600248856006900264 2004 eng d00aThe ABCs of Computerized Adaptive Testing0 aABCs of Computerized Adaptive Testing aT. M. Wood and W. Zhi (Eds.), Measurement issues and practice in physical activity. Champaign, IL: Human kinetics.1 aGershon, RC uhttp://mail.iacat.org/content/abcs-computerized-adaptive-testing02594nas a2200469 4500008004100000245007200041210006900113300001000182490000600192520108600198653002501284653001001309653001501319653002101334653002201355653005901377653007001436653003301506653001101539653001101550653001301561653000901574653002701583653002201610653005501632653001901687653001501706653006601721653001801787653003701805653004101842653003001883653001301913100001501926700001301941700001801954700001501972700001401987700001402001700001302015856009602028 2004 eng d00aComputerized adaptive measurement of depression: A simulation study0 aComputerized adaptive measurement of depression A simulation stu a13-230 v43 aBackground: Efficient, accurate instruments for measuring depression are increasingly importantin clinical practice. We developed a computerized adaptive version of the Beck DepressionInventory (BDI). We examined its efficiency and its usefulness in identifying Major DepressiveEpisodes (MDE) and in measuring depression severity.Methods: Subjects were 744 participants in research studies in which each subject completed boththe BDI and the SCID. In addition, 285 patients completed the Hamilton Depression Rating Scale.Results: The adaptive BDI had an AUC as an indicator of a SCID diagnosis of MDE of 88%,equivalent to the full BDI. The adaptive BDI asked fewer questions than the full BDI (5.6 versus 21items). The adaptive latent depression score correlated r = .92 with the BDI total score and thelatent depression score correlated more highly with the Hamilton (r = .74) than the BDI total scoredid (r = .70).Conclusions: Adaptive testing for depression may provide greatly increased efficiency withoutloss of accuracy in identifying MDE or in measuring depression severity.10a*Computer Simulation10aAdult10aAlgorithms10aArea Under Curve10aComparative Study10aDepressive Disorder/*diagnosis/epidemiology/psychology10aDiagnosis, Computer-Assisted/*methods/statistics & numerical data10aFactor Analysis, Statistical10aFemale10aHumans10aInternet10aMale10aMass Screening/methods10aPatient Selection10aPersonality Inventory/*statistics & numerical data10aPilot Projects10aPrevalence10aPsychiatric Status Rating Scales/*statistics & numerical data10aPsychometrics10aResearch Support, Non-U.S. Gov't10aResearch Support, U.S. Gov't, P.H.S.10aSeverity of Illness Index10aSoftware1 aGardner, W1 aShear, K1 aKelleher, K J1 aPajer, K A1 aMammen, O1 aBuysse, D1 aFrank, E uhttp://mail.iacat.org/content/computerized-adaptive-measurement-depression-simulation-study00427nas 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-system00717nas a2200205 4500008004100000020002200041245010800063210006900171260003300240300000900273490000900282100002400291700002300315700002700338700002900365700002100394700002300415700002300438856005000461 2004 eng d a978-3-540-22948-300aA Learning Environment for English for Academic Purposes Based on Adaptive Tests and Task-Based Systems0 aLearning Environment for English for Academic Purposes Based on  bSpringer Berlin / Heidelberg a1-110 v32201 aGonçalves, Jean, P1 aAluisio, Sandra, M1 aOliveira, Leandro, H M1 aOliveira Jr., Osvaldo, N1 aLester, James, C1 aVicari, Rosa Maria1 aParaguaçu, Fábio uhttp://dx.doi.org/10.1007/978-3-540-30139-4_102844nas a2200349 4500008004100000020004600041245011400087210006900201250001500270260001100285300000700296490000600303520169400309653002702003653002002030653002102050653002002071653004702091653003702138653001802175653001102193653001902204653001602223653002002239653003002259100001402289700001402303700001702317700002002334700001402354856012602368 2004 eng d a1477-7525 (Electronic)1477-7525 (Linking)00aPractical methods for dealing with 'not applicable' item responses in the AMC Linear Disability Score project0 aPractical methods for dealing with not applicable item responses a2004/06/18 cJun 16 a290 v23 aBACKGROUND: Whenever questionnaires are used to collect data on constructs, such as functional status or health related quality of life, it is unlikely that all respondents will respond to all items. This paper examines ways of dealing with responses in a 'not applicable' category to items included in the AMC Linear Disability Score (ALDS) project item bank. METHODS: The data examined in this paper come from the responses of 392 respondents to 32 items and form part of the calibration sample for the ALDS item bank. The data are analysed using the one-parameter logistic item response theory model. The four practical strategies for dealing with this type of response are: cold deck imputation; hot deck imputation; treating the missing responses as if these items had never been offered to those individual patients; and using a model which takes account of the 'tendency to respond to items'. RESULTS: The item and respondent population parameter estimates were very similar for the strategies involving hot deck imputation; treating the missing responses as if these items had never been offered to those individual patients; and using a model which takes account of the 'tendency to respond to items'. The estimates obtained using the cold deck imputation method were substantially different. CONCLUSIONS: The cold deck imputation method was not considered suitable for use in the ALDS item bank. The other three methods described can be usefully implemented in the ALDS item bank, depending on the purpose of the data analysis to be carried out. These three methods may be useful for other data sets examining similar constructs, when item response theory based methods are used.10a*Disability Evaluation10a*Health Surveys10a*Logistic Models10a*Questionnaires10aActivities of Daily Living/*classification10aData Interpretation, Statistical10aHealth Status10aHumans10aPilot Projects10aProbability10aQuality of Life10aSeverity of Illness Index1 aHolman, R1 aGlas, C A1 aLindeboom, R1 aZwinderman, A H1 aHaan, R J uhttp://mail.iacat.org/content/practical-methods-dealing-not-applicable-item-responses-amc-linear-disability-score-project00542nas a2200181 4500008004100000245005000041210004800091300001000139490000700149653003400156100001400190700001500204700001500219700001400234700002600248700001300274856007300287 2004 eng d00aSiette: a web-based tool for adaptive testing0 aSiette a webbased tool for adaptive testing a29-610 v1410acomputerized adaptive testing1 aConejo, R1 aGuzmán, E1 aMillán, E1 aTrella, M1 aPérez-De-La-Cruz, JL1 aRíos, A uhttp://mail.iacat.org/content/siette-web-based-tool-adaptive-testing00607nas a2200109 4500008004100000245009200041210006900133260014600202100001800348700001900366856011200385 2004 eng d00aState-of-the-art and adaptive open-closed items in adaptive foreign language assessment0 aStateoftheart and adaptive openclosed items in adaptive foreign  aProceedings 4th Hellenic Conference with ternational Participation: Informational and Communication Technologies in Education, Athens,747-7561 aGiouroglou, H1 aEconomides, AA uhttp://mail.iacat.org/content/state-art-and-adaptive-open-closed-items-adaptive-foreign-language-assessment01419nas a2200145 4500008004100000245007600041210006900117260000800186300001200194490000700206520092600213100001401139700001701153856010301170 2004 eng d00aTesting vocabulary knowledge: Size, strength, and computer adaptiveness0 aTesting vocabulary knowledge Size strength and computer adaptive cSep a399-4360 v543 a(from the journal abstract) In this article, we describe the development and trial of a bilingual computerized test of vocabulary size, the number of words the learner knows, and strength, a combination of four aspects of knowledge of meaning that are assumed to constitute a hierarchy of difficulty: passive recognition (easiest), active recognition, passive recall, and active recall (hardest). The participants were 435 learners of English as a second language. We investigated whether the above hierarchy was valid and which strength modality correlated best with classroom language performance. Results showed that the hypothesized hierarchy was present at all word frequency levels, that passive recall was the best predictor of classroom language performance, and that growth in vocabulary knowledge was different for the different strength modalities. (PsycINFO Database Record (c) 2004 APA, all rights reserved).1 aLaufer, B1 aGoldstein, Z uhttp://mail.iacat.org/content/testing-vocabulary-knowledge-size-strength-and-computer-adaptiveness00434nas a2200109 4500008004100000245004900041210004900090260007200139100001800211700001900229856007600248 2003 eng d00aCognitive CAT in foreign language assessment0 aCognitive CAT in foreign language assessment aPowerful ICT Tools for Learning and Teaching, PEG '03, CD-ROM, 20031 aGiouroglou, H1 aEconomides, AA uhttp://mail.iacat.org/content/cognitive-cat-foreign-language-assessment01762nas a2200313 4500008004100000245007700041210006900118300001200187490000700199520083400206653002101040653001501061653001701076653001601093653003001109653001701139653001501156653002501171653002001196653001501216653002501231653001801256653000901274100001801283700001201301700001601313700001601329856010301345 2003 eng d00aComputerized adaptive rating scales for measuring managerial performance0 aComputerized adaptive rating scales for measuring managerial per a237-2460 v113 aComputerized adaptive rating scales (CARS) had been developed to measure contextual or citizenship performance. This rating format used a paired-comparison protocol, presenting pairs of behavioral statements scaled according to effectiveness levels, and an iterative item response theory algorithm to obtain estimates of ratees' citizenship performance (W. C. Borman et al, 2001). In the present research, we developed CARS to measure the entire managerial performance domain, including task and citizenship performance, thus addressing a major limitation of the earlier CARS. The paper describes this development effort, including an adjustment to the algorithm that reduces substantially the number of item pairs required to obtain almost as much precision in the performance estimates. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aAlgorithms10aAssociations10aCitizenship10aComputer Assisted Testing10aConstruction10aContextual10aItem Response Theory10aJob Performance10aManagement10aManagement Personnel10aRating Scales10aTest1 aSchneider, RJ1 aGoff, M1 aAnderson, S1 aBorman, W C uhttp://mail.iacat.org/content/computerized-adaptive-rating-scales-measuring-managerial-performance01592nas a2200145 4500008004100000245005200041210005200093300001200145490000700157520113200164653003401296100001601330700002301346856007701369 2003 eng d00aComputerized adaptive testing with item cloning0 aComputerized adaptive testing with item cloning a247-2610 v273 a(from the journal abstract) To increase the number of items available for adaptive testing and reduce the cost of item writing, the use of techniques of item cloning has been proposed. An important consequence of item cloning is possible variability between the item parameters. To deal with this variability, a multilevel item response (IRT) model is presented which allows for differences between the distributions of item parameters of families of item clones. A marginal maximum likelihood and a Bayesian procedure for estimating the hyperparameters are presented. In addition, an item-selection procedure for computerized adaptive testing with item cloning is presented which has the following two stages: First, a family of item clones is selected to be optimal at the estimate of the person parameter. Second, an item is randomly selected from the family for administration. Results from simulation studies based on an item pool from the Law School Admission Test (LSAT) illustrate the accuracy of these item pool calibration and adaptive testing procedures. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aGlas, C A W1 avan der Linden, WJ uhttp://mail.iacat.org/content/computerized-adaptive-testing-item-cloning00510nas a2200121 4500008004100000245009900041210006900140100001300209700001600222700001800238700001500256856011700271 2003 eng d00aDevelopment and psychometric evaluation of the Flexilevel Scale of Shoulder Function (FLEX-SF)0 aDevelopment and psychometric evaluation of the Flexilevel Scale 1 aCook, KF1 aRoddey, T S1 aGartsman, G M1 aOlson, S L uhttp://mail.iacat.org/content/development-and-psychometric-evaluation-flexilevel-scale-shoulder-function-flex-sf00525nas a2200109 4500008004100000245014200041210006900183260001500252100001300267700001300280856012200293 2003 eng d00aEvaluating the comparability of English- and French-speaking examinees on a science achievement test administered using two-stage testing0 aEvaluating the comparability of English and Frenchspeaking exami aChicago IL1 aPuhan, G1 aGierl, M uhttp://mail.iacat.org/content/evaluating-comparability-english-and-french-speaking-examinees-science-achievement-test00394nas 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-program00404nas a2200097 4500008004100000245006100041210005900102260004100161100001600202856008800218 2003 eng d00aStandard-setting issues in computerized-adaptive testing0 aStandardsetting issues in computerizedadaptive testing aHalifax, Nova Scotia, May 30th, 20031 aGushta, M M uhttp://mail.iacat.org/content/standard-setting-issues-computerized-adaptive-testing00467nas a2200109 4500008004100000245008400041210006900125260001900194100001600213700001700229856011100246 2002 eng d00aContent-stratified random item selection in computerized classification testing0 aContentstratified random item selection in computerized classifi aNew Orleans LA1 aGuille, R S1 aNorcini, J J uhttp://mail.iacat.org/content/content-stratified-random-item-selection-computerized-classification-testing02792nas a2200133 4500008004100000245010200041210006900143300000900212490000700221520226500228653003402493100002002527856011102547 2002 eng d00aThe implications of the use of non-optimal items in a Computer Adaptive Testing (CAT) environment0 aimplications of the use of nonoptimal items in a Computer Adapti a16060 v633 aThis study describes the effects of manipulating item difficulty in a computer adaptive testing (CAT) environment. There are many potential benefits when using CATS as compared to traditional tests. These include increased security, shorter tests, and more precise measurement. According to IRT, the theory underlying CAT, as the computer continually recalculates ability, items that match that current estimate of ability are administered. Such items provide maximum information about examinees during the test. Herein, however, lies a potential problem. These optimal CAT items result in an examinee having only a 50% chance of a correct response. Some examinees may consider such items unduly challenging. Further, when test anxiety is a factor, it is possible that test scores may be negatively affected. This research was undertaken to determine the effects of administering easier CAT items on ability estimation and test length using computer simulations. Also considered was the administration of different numbers of initial items prior to the start of the adaptive portion of the test, using three different levels of measurement precision. Results indicate that regardless of the number of initial items administered, the level of precision employed, or the modifications made to item difficulty, the approximation of estimated ability to true ability is good in all cases. Additionally, the standard deviations of the ability estimates closely approximate the theoretical levels of precision used as stopping rules for the simulated CATs. Since optimal CAT items are not used, each item administered provides less information about examinees than optimal CAT items. This results in longer tests. Fortunately, using easier items that provide up to a 66.4% chance of a correct response results in tests that only modestly increase in length, across levels of precision. For larger standard errors, even easier items (up to a 73.5% chance of a correct response) result in only negligible to modest increases in test length. Examinees who find optimal CAT items difficult or examinees with test anxiety may find CATs that implement easier items enhance the already existing benefits of CAT. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aGrodenchik, D J uhttp://mail.iacat.org/content/implications-use-non-optimal-items-computer-adaptive-testing-cat-environment03063nas a2200325 4500008004100000020004100041245008100082210006900163250001500232260000800247300001100255490000700266520201300273653001502286653001002301653004002311653005702351653003302408653001102441653001102452653001802463653000902481653002802490653001202518653005502530100001502585700001802600700001502618856010402633 2002 eng d a0025-7079 (Print)0025-7079 (Linking)00aMultidimensional adaptive testing for mental health problems in primary care0 aMultidimensional adaptive testing for mental health problems in  a2002/09/10 cSep a812-230 v403 aOBJECTIVES: Efficient and accurate instruments for assessing child psychopathology are increasingly important in clinical practice and research. For example, screening in primary care settings can identify children and adolescents with disorders that may otherwise go undetected. However, primary care offices are notorious for the brevity of visits and screening must not burden patients or staff with long questionnaires. One solution is to shorten assessment instruments, but dropping questions typically makes an instrument less accurate. An alternative is adaptive testing, in which a computer selects the items to be asked of a patient based on the patient's previous responses. This research used a simulation to test a child mental health screen based on this technology. RESEARCH DESIGN: Using half of a large sample of data, a computerized version was developed of the Pediatric Symptom Checklist (PSC), a parental-report psychosocial problem screen. With the unused data, a simulation was conducted to determine whether the Adaptive PSC can reproduce the results of the full PSC with greater efficiency. SUBJECTS: PSCs were completed by parents on 21,150 children seen in a national sample of primary care practices. RESULTS: Four latent psychosocial problem dimensions were identified through factor analysis: internalizing problems, externalizing problems, attention problems, and school problems. A simulated adaptive test measuring these traits asked an average of 11.6 questions per patient, and asked five or fewer questions for 49% of the sample. There was high agreement between the adaptive test and the full (35-item) PSC: only 1.3% of screening decisions were discordant (kappa = 0.93). This agreement was higher than that obtained using a comparable length (12-item) short-form PSC (3.2% of decisions discordant; kappa = 0.84). CONCLUSIONS: Multidimensional adaptive testing may be an accurate and efficient technology for screening for mental health problems in primary care settings.10aAdolescent10aChild10aChild Behavior Disorders/*diagnosis10aChild Health Services/*organization & administration10aFactor Analysis, Statistical10aFemale10aHumans10aLinear Models10aMale10aMass Screening/*methods10aParents10aPrimary Health Care/*organization & administration1 aGardner, W1 aKelleher, K J1 aPajer, K A uhttp://mail.iacat.org/content/multidimensional-adaptive-testing-mental-health-problems-primary-care00486nas a2200097 4500008004100000245009100041210006900132260005800201100001800259856011100277 2001 eng d00aCB BULATS: Examining the reliability of a computer based test using test-retest method0 aCB BULATS Examining the reliability of a computer based test usi aCambridge ESOL Research Notes, Issue 5, July 2001, pp1 aGeranpayeh, A uhttp://mail.iacat.org/content/cb-bulats-examining-reliability-computer-based-test-using-test-retest-method00427nas a2200121 4500008004100000245005900041210005900100260001500159100001700174700001900191700001200210856008300222 2001 eng d00aDeriving a stopping rule for sequential adaptive tests0 aDeriving a stopping rule for sequential adaptive tests aSeattle WA1 aGrabovsky, I1 aChang, Hua-Hua1 aYing, Z uhttp://mail.iacat.org/content/deriving-stopping-rule-sequential-adaptive-tests00427nas a2200121 4500008004100000245006500041210006500106260001500171100001100186700001100197700001100208856008600219 2001 eng d00aImpact of item location effects on ability estimation in CAT0 aImpact of item location effects on ability estimation in CAT aSeattle WA1 aLiu, M1 aZhu, R1 aGuo, F uhttp://mail.iacat.org/content/impact-item-location-effects-ability-estimation-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-scores00382nas a2200109 4500008004100000245005100041210005100092260001500143100001600158700002300174856007500197 2001 eng d00aModeling variability in item parameters in CAT0 aModeling variability in item parameters in CAT aSeattle WA1 aGlas, C A W1 avan der Linden, WJ uhttp://mail.iacat.org/content/modeling-variability-item-parameters-cat00425nas a2200109 4500008004100000245006700041210006600108260001500174100001300189700001600202856009700218 2001 eng d00aMultidimensional IRT-based adaptive sequential mastery testing0 aMultidimensional IRTbased adaptive sequential mastery testing aSeattle WA1 aVos, H J1 aGlas, C E W uhttp://mail.iacat.org/content/multidimensional-irt-based-adaptive-sequential-mastery-testing01860nas a2200193 4500008004100000245012400041210007100165300001200236490000700248520110700255653002101362653002601383653002201409653001401431653005901445100001601504700001701520856012901537 2001 eng d00aNouveaux développements dans le domaine du testing informatisé [New developments in the area of computerized testing]0 aNouveaux développements dans le domaine du testing informatisé N a221-2300 v463 aL'usage de l'évaluation assistée par ordinateur s'est fortement développé depuis la première formulation de ses principes de base dans les années soixante et soixante-dix. Cet article offre une introduction aux derniers développements dans le domaine de l'évaluation assistée par ordinateur, en particulier celui du testing adaptative informatisée (TAI). L'estimation de l'aptitude, la sélection des items et le développement d'une base d'items dans le cas du TAI sont discutés. De plus, des exemples d'utilisations innovantes de l'ordinateur dans des systèmes intégrés de testing et de testing via Internet sont présentés. L'article se termine par quelques illustrations de nouvelles applications du testing informatisé et des suggestions pour des recherches futures.Discusses the latest developments in computerized psychological assessment, with emphasis on computerized adaptive testing (CAT). Ability estimation, item selection, and item pool development in CAT are described. Examples of some innovative approaches to CAT are presented. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Applications10aComputer Assisted10aDiagnosis10aPsychological Assessment computerized adaptive testing1 aMeijer, R R1 aGrégoire, J uhttp://mail.iacat.org/content/nouveaux-d%C3%A9veloppements-dans-le-domaine-du-testing-informatis%C3%A9-new-developments-area00522nas a2200121 4500008004100000245010800041210006900149260002400218100001100242700001300253700001200266856012200278 2001 eng d00aOn-line Calibration Using PARSCALE Item Specific Prior Method: Changing Test Population and Sample Size0 aOnline Calibration Using PARSCALE Item Specific Prior Method Cha aSeattle, Washington1 aGuo, F1 aStone, E1 aCruz, D uhttp://mail.iacat.org/content/line-calibration-using-parscale-item-specific-prior-method-changing-test-population-and00532nas 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-01-2000646nas a2200109 4500008004100000245012800041210006900169260014400238100001600382700001300398856012500411 2000 eng d00aAdaptive mastery testing using a multidimensional IRT model and Bayesian sequential decision theory (Research Report 00-06)0 aAdaptive mastery testing using a multidimensional IRT model and  aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aGlas, C A W1 aVos, H J uhttp://mail.iacat.org/content/adaptive-mastery-testing-using-multidimensional-irt-model-and-bayesian-sequential-decision01261nas a2200145 4500008004100000245006500041210006500106300001000171490000700181520076500188653003400953100002300987700001601010856008901026 2000 eng d00aCapitalization on item calibration error in adaptive testing0 aCapitalization on item calibration error in adaptive testing a35-530 v133 a(from the journal abstract) In adaptive testing, item selection is sequentially optimized during the test. Because the optimization takes place over a pool of items calibrated with estimation error, capitalization on chance is likely to occur. How serious the consequences of this phenomenon are depends not only on the distribution of the estimation errors in the pool or the conditional ratio of the test length to the pool size given ability, but may also depend on the structure of the item selection criterion used. A simulation study demonstrated a dramatic impact of capitalization on estimation errors on ability estimation. Four different strategies to minimize the likelihood of capitalization on error in computerized adaptive testing are discussed.10acomputerized adaptive testing1 avan der Linden, WJ1 aGlas, C A W uhttp://mail.iacat.org/content/capitalization-item-calibration-error-adaptive-testing01588nas a2200241 4500008004100000245005800041210005800099300001200157490000600169520081000175653001400985653001400999653004801013653005701061653001101118653001801129653003101147653003701178100001301215700001701228700001601245856008501261 2000 eng d00aCAT administration of language placement examinations0 aCAT administration of language placement examinations a292-3020 v13 aThis article describes the development of a computerized adaptive test for Cegep de Jonquiere, a community college located in Quebec, Canada. Computerized language proficiency testing allows the simultaneous presentation of sound stimuli as the question is being presented to the test-taker. With a properly calibrated bank of items, the language proficiency test can be offered in an adaptive framework. By adapting the test to the test-taker's level of ability, an assessment can be made with significantly fewer items. We also describe our initial attempt to detect instances in which "cheating low" is occurring. In the "cheating low" situation, test-takers deliberately answer questions incorrectly, questions that they are fully capable of answering correctly had they been taking the test honestly.10a*Language10a*Software10aAptitude Tests/*statistics & numerical data10aEducational Measurement/*statistics & numerical data10aHumans10aPsychometrics10aReproducibility of Results10aResearch Support, Non-U.S. Gov't1 aStahl, J1 aBergstrom, B1 aGershon, RC uhttp://mail.iacat.org/content/cat-administration-language-placement-examinations00588nam 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-edition00442nam a2200109 4500008004100000245005500041210005400096260005900150100002300209700001600232856008400248 2000 eng d00aComputerized adaptive testing: Theory and practice0 aComputerized adaptive testing Theory and practice aDordrecht, The NetherlandsbKluwer Academic Publishers1 avan der Linden, WJ1 aGlas, C A W uhttp://mail.iacat.org/content/computerized-adaptive-testing-theory-and-practice00549nas a2200109 4500008004100000245006700041210006600108260013200174100002300306700001600329856009400345 2000 eng d00aCross-validating item parameter estimation in adaptive testing0 aCrossvalidating item parameter estimation in adaptive testing aA. Boorsma, M. A. J. van Duijn, and T. A. B. Snijders (Eds.) (pp. 205-219), Essays on item response theory. New York: Springer.1 avan der Linden, WJ1 aGlas, C A W uhttp://mail.iacat.org/content/cross-validating-item-parameter-estimation-adaptive-testing00486nas a2200121 4500008004100000245009100041210006900132300001200201490000700213100002000220700001600240856010800256 2000 eng d00aDetection of known items in adaptive testing with a statistical quality control method0 aDetection of known items in adaptive testing with a statistical  a373-3890 v251 aVeerkamp, W J J1 aGlas, C E W uhttp://mail.iacat.org/content/detection-known-items-adaptive-testing-statistical-quality-control-method00453nas a2200097 4500008004100000245004100041210004100082260014500123100001600268856007100284 2000 eng d00aItem calibration and parameter drift0 aItem calibration and parameter drift aW. J. van der linden and C. A. W. Glas (Eds.). Computerized adaptive testing: Theory and practice (pp.183-199). Norwell MA: Kluwer Academic.1 aGlas, C A W uhttp://mail.iacat.org/content/item-calibration-and-parameter-drift01344nas a2200157 4500008004100000245006300041210006300104300001000167490000700177520083100184100002101015700001801036700002001054700002201074856009001096 2000 eng d00aItem selection algorithms in computerized adaptive testing0 aItem selection algorithms in computerized adaptive testing a12-140 v123 aStudied the efficacy of 3 different item selection algorithms in computerized adaptive testing. Ss were 395 university students (aged 20-25 yrs) in Spain. Ss were asked to submit answers via computer to 28 items of a personality questionnaire using item selection algorithms based on maximum item information, entropy, or mixed item-entropy algorithms. The results were evaluated according to ability of Ss to use item selection algorithms and number of questions. Initial results indicate that mixed criteria algorithms were more efficient than information or entropy algorithms for up to 15 questionnaire items, but that differences in efficiency decreased with increasing item number. Implications for developing computer adaptive testing methods are discussed. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aGarcia, David, A1 aSanta Cruz, C1 aDorronsoro, J R1 aRubio Franco, V J uhttp://mail.iacat.org/content/item-selection-algorithms-computerized-adaptive-testing00499nas 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-testing00422nas 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-tests00460nas a2200109 4500008004100000245004600041210004400087260011500131100001300246700001600259856007500275 2000 eng d00aTestlet-based adaptive mastery testing, W0 aTestletbased adaptive mastery testing W aJ. van der Linden (Ed.), Computerized adaptive testing: Theory and practice (pp. 289-309). Norwell MA: Kluwer.1 aVos, H J1 aGlas, C A W uhttp://mail.iacat.org/content/testlet-based-adaptive-mastery-testing-w00410nas a2200121 4500008004100000245005100041210005100092260002100143100001300164700001600177700001700193856007800210 1999 eng d00aCAT administration of language placement exams0 aCAT administration of language placement exams aMontreal, Canada1 aStahl, J1 aGershon, RC1 aBergstrom, B uhttp://mail.iacat.org/content/cat-administration-language-placement-exams02156nas a2200277 4500008004100000020002200041245009600063210006900159250001500228260000800243300001100251490000700262520122800269653001601497653003901513653003701552653001101589653003301600653002501633653002701658653003101685100001701716700001601733700001701749856011201766 1999 eng d a1040-2446 (Print)00aEvaluating the usefulness of computerized adaptive testing for medical in-course assessment0 aEvaluating the usefulness of computerized adaptive testing for m a1999/10/28 cOct a1125-80 v743 aPURPOSE: This study investigated the feasibility of converting an existing computer-administered, in-course internal medicine test to an adaptive format. METHOD: A 200-item internal medicine extended matching test was used for this research. Parameters were estimated with commercially available software with responses from 621 examinees. A specially developed simulation program was used to retrospectively estimate the efficiency of the computer-adaptive exam format. RESULTS: It was found that the average test length could be shortened by almost half with measurement precision approximately equal to that of the full 200-item paper-and-pencil test. However, computer-adaptive testing with this item bank provided little advantage for examinees at the upper end of the ability continuum. An examination of classical item statistics and IRT item statistics suggested that adding more difficult items might extend the advantage to this group of examinees. CONCLUSIONS: Medical item banks presently used for incourse assessment might be advantageously employed in adaptive testing. However, it is important to evaluate the match between the items and the measurement objective of the test before implementing this format.10a*Automation10a*Education, Medical, Undergraduate10aEducational Measurement/*methods10aHumans10aInternal Medicine/*education10aLikelihood Functions10aPsychometrics/*methods10aReproducibility of Results1 aKreiter, C D1 aFerguson, K1 aGruppen, L D uhttp://mail.iacat.org/content/evaluating-usefulness-computerized-adaptive-testing-medical-course-assessment00379nas a2200121 4500008004100000245003900041210003800080260002100118100002000139700001700159700001500176856006600191 1999 eng d00aFairness in computer-based testing0 aFairness in computerbased testing aMontreal, Canada1 aGallagher, Aand1 aBridgeman, B1 aCalahan, C uhttp://mail.iacat.org/content/fairness-computer-based-testing00461nas a2200109 4500008004100000245004100041210004100082260011900123100001600242700002000258856007300278 1999 eng d00aItem calibration and parameter drift0 aItem calibration and parameter drift aW. J. van der Linden and C. A. W. Glas (Eds.), Computer adaptive testing: Theory and practice. Norwell MA: Kluwer.1 aGlas, C A W1 aVeerkamp, W J J uhttp://mail.iacat.org/content/item-calibration-and-parameter-drift-000374nas a2200097 4500008004100000245006100041210006100102260002100163100001100184856008100195 1999 eng d00aManaging CAT item development in the face of uncertainty0 aManaging CAT item development in the face of uncertainty aMontreal, Canada1 aGuo, F uhttp://mail.iacat.org/content/managing-cat-item-development-face-uncertainty00634nas a2200109 4500008004100000245011500041210006900156260014400225100001600369700001300385856012600398 1998 eng d00aAdaptive mastery testing using the Rasch model and Bayesian sequential decision theory (Research Report 98-15)0 aAdaptive mastery testing using the Rasch model and Bayesian sequ aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aGlas, C A W1 aVos, H J uhttp://mail.iacat.org/content/adaptive-mastery-testing-using-rasch-model-and-bayesian-sequential-decision-theory-research00603nas a2200109 4500008004100000245008900041210006900130260014400199100002300343700001600366856011100382 1998 eng d00aCapitalization on item calibration error in adaptive testing (Research Report 98-07)0 aCapitalization on item calibration error in adaptive testing Res aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 avan der Linden, WJ1 aGlas, C A W uhttp://mail.iacat.org/content/capitalization-item-calibration-error-adaptive-testing-research-report-98-0700730nas a2200157 4500008004100000245018900041210006900230260004700299100001700346700001700363700002100380700001300401700001700414700001500431856012600446 1998 eng d00aComparability of paper-and-pencil and computer adaptive test scores on the GRE General Test (GRE Board Professional Report No 95-08P; Educational Testing Service Research Report 98-38)0 aComparability of paperandpencil and computer adaptive test score aPrinceton, NJ: Educational Testing Service1 aSchaeffer, G1 aBridgeman, B1 aGolub-Smith, M L1 aLewis, C1 aPotenza, M T1 aSteffen, M uhttp://mail.iacat.org/content/comparability-paper-and-pencil-and-computer-adaptive-test-scores-gre-general-test-gre-board00688nas a2200169 4500008004100000020003000041245009600071210006900167260006400236100001900300700001700319700002100336700001300357700001700370700001500387856011600402 1998 eng d aETS Research Report 98-3800aComparability of paper-and-pencil and computer adaptive test scores on the GRE General Test0 aComparability of paperandpencil and computer adaptive test score aPrinceton, N.J.bEducational Testing ServicescAugust, 19981 aSchaeffer, G A1 aBridgeman, B1 aGolub-Smith, M L1 aLewis, C1 aPotenza, M T1 aSteffen, M uhttp://mail.iacat.org/content/comparability-paper-and-pencil-and-computer-adaptive-test-scores-gre-general-test00587nas a2200097 4500008004100000245010000041210006900141260014400210100001600354856011900370 1998 eng d00aQuality control of on-line calibration in computerized adaptive testing (Research Report 98-03)0 aQuality control of online calibration in computerized adaptive t aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aGlas, C A W uhttp://mail.iacat.org/content/quality-control-line-calibration-computerized-adaptive-testing-research-report-98-0300651nas a2200121 4500008004100000245009700041210006900138260014500207100001600352700001600368700002700384856011800411 1998 eng d00aStatistical tests for person misfit in computerized adaptive testing (Research Report 98-01)0 aStatistical tests for person misfit in computerized adaptive tes aEnschede, The Netherlands : University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aGlas, C A W1 aMeijer, R R1 aKrimpen-Stoop, E M L A uhttp://mail.iacat.org/content/statistical-tests-person-misfit-computerized-adaptive-testing-research-report-98-0100597nas a2200145 4500008004100000020001000041245007300051210006900124260010000193300000700293100001600300700001600316700002300332856009600355 1998 eng d a98-0100aStatistical tests for person misfit in computerized adaptive testing0 aStatistical tests for person misfit in computerized adaptive tes aEnschede, The NetherlandsbFaculty of Educational Science and Technology, Univeersity of Twente a281 aGlas, C A W1 aMeijer, R R1 aKrimpen-Stoop, E M uhttp://mail.iacat.org/content/statistical-tests-person-misfit-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-test00383nas a2200097 4500008004100000245006300041210006200104260001500166100001400181856009000195 1997 eng d00aAlternate methods of scoring computer-based adaptive tests0 aAlternate methods of scoring computerbased adaptive tests aChicago IL1 aGreen, BF uhttp://mail.iacat.org/content/alternate-methods-scoring-computer-based-adaptive-tests00458nas a2200121 4500008004100000245006900041210006700110260001500177100001600192700001600208700001600224856009600240 1997 eng d00aAssessing speededness in variable-length computer-adaptive tests0 aAssessing speededness in variablelength computeradaptive tests aChicago IL1 aBontempo, B1 aJulian, E R1 aGorham, J L uhttp://mail.iacat.org/content/assessing-speededness-variable-length-computer-adaptive-tests02025nas a2200289 4500008004100000245012700041210006900168300001300237490000800250520105800258653003401316653003301350653002301383653001501406653001001421653002601431653001001457653001501467653001801482653003101500100001501531700001601546700001401562700001701576700001601593856012601609 1997 eng d00aA computerized adaptive testing system for speech discrimination measurement: The Speech Sound Pattern Discrimination Test0 acomputerized adaptive testing system for speech discrimination m a2289-2980 v1013 aA computerized, adaptive test-delivery system for the measurement of speech discrimination, the Speech Sound Pattern Discrimination Test, is described and evaluated. Using a modified discrimination task, the testing system draws on a pool of 130 items spanning a broad range of difficulty to estimate an examinee's location along an underlying continuum of speech processing ability, yet does not require the examinee to possess a high level of English language proficiency. The system is driven by a mathematical measurement model which selects only test items which are appropriate in difficulty level for a given examinee, thereby individualizing the testing experience. Test items were administered to a sample of young deaf adults, and the adaptive testing system evaluated in terms of respondents' sensory and perceptual capabilities, acoustic and phonetic dimensions of speech, and theories of speech perception. Data obtained in this study support the validity, reliability, and efficiency of this test as a measure of speech processing ability.10a*Diagnosis, Computer-Assisted10a*Speech Discrimination Tests10a*Speech Perception10aAdolescent10aAdult10aAudiometry, Pure-Tone10aHuman10aMiddle Age10aPsychometrics10aReproducibility of Results1 aBochner, J1 aGarrison, W1 aPalmer, L1 aMacKenzie, D1 aBraveman, A uhttp://mail.iacat.org/content/computerized-adaptive-testing-system-speech-discrimination-measurement-speech-sound-pattern00476nas a2200133 4500008004100000245007300041210006900114300001000183490000700193100001300200700001100213700001800224856010000242 1997 eng d00aDeveloping and scoring an innovative computerized writing assessment0 aDeveloping and scoring an innovative computerized writing assess a21-410 v341 aDavey, T1 aGodwin1 aMittelholz, D uhttp://mail.iacat.org/content/developing-and-scoring-innovative-computerized-writing-assessment00705nas a2200121 4500008004100000245007200041210006900113260025200182100001700434700001500451700001500466856010200481 1996 eng d00aAdaptive assessment using granularity hierarchies and Bayesian nets0 aAdaptive assessment using granularity hierarchies and Bayesian n aFrasson, C. and Gauthier, G. and Lesgold, A. (Eds.) Intelligent Tutoring Systems, Third International Conference, ITS'96, Montréal, Canada, June 1996 Proceedings. Lecture Notes in Computer Science 1086. Berlin Heidelberg: Springer-Verlag 569-577.1 aCollins, J A1 aGreer, J E1 aHuang, S X uhttp://mail.iacat.org/content/adaptive-assessment-using-granularity-hierarchies-and-bayesian-nets02614nas a2200133 4500008004100000245011400041210006900155300000900224490000700233520206700240653003402307100001602341856012302357 1996 eng d00aThe effect of individual differences variables on the assessment of ability for Computerized Adaptive Testing0 aeffect of individual differences variables on the assessment of  a40850 v573 aComputerized Adaptive Testing (CAT) continues to gain momentum as the accepted testing modality for a growing number of certification, licensure, education, government and human resource applications. However, the developers of these tests have for the most part failed to adequately explore the impact of individual differences such as test anxiety on the adaptive testing process. It is widely accepted that non-cognitive individual differences variables interact with the assessment of ability when using written examinations. Logic would dictate that individual differences variables would equally affect CAT. Two studies were used to explore this premise. In the first study, 507 examinees were given a test anxiety survey prior to taking a high stakes certification exam using CAT or using a written format. All examinees had already completed their course of study, and the examination would be their last hurdle prior to being awarded certification. High test anxious examinees performed worse than their low anxious counterparts on both testing formats. The second study replicated the finding that anxiety depresses performance in CAT. It also addressed the differential effect of anxiety on within test performance. Examinees were candidates taking their final certification examination following a four year college program. Ability measures were calculated for each successive part of the test for 923 subjects. Within subject performance varied depending upon test position. High anxious examinees performed poorly at all points in the test, while low and medium anxious examinee performance peaked in the middle of the test. If test anxiety and performance measures were actually the same trait, then low anxious individuals should have performed equally well throughout the test. The observed interaction of test anxiety and time on task serves as strong evidence that test anxiety has motivationally mediated as well as cognitively mediated effects. The results of the studies are di (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aGershon, RC uhttp://mail.iacat.org/content/effect-individual-differences-variables-assessment-ability-computerized-adaptive-testing00585nas a2200133 4500008004100000245013900041210006900180260001600249100001100265700001200276700001700288700002100305856012500326 1996 eng d00aThe effects of methods of theta estimation, prior distribution, and number of quadrature points on CAT using the graded response model0 aeffects of methods of theta estimation prior distribution and nu aNew York NY1 aHou, L1 aChen, S1 aG., Dodd., B1 aFitzpatrick, S J uhttp://mail.iacat.org/content/effects-methods-theta-estimation-prior-distribution-and-number-quadrature-points-cat-using00446nas a2200121 4500008004100000245007300041210006900114300001200183490000700195100001300202700001400215856009500229 1995 eng d00aA comparison of item selection routines in linear and adaptive tests0 acomparison of item selection routines in linear and adaptive tes a227-2420 v321 aSchnipke1 aGreen, BF uhttp://mail.iacat.org/content/comparison-item-selection-routines-linear-and-adaptive-tests00329nas a2200109 4500008004100000245003400041210003300075260001800108100001600126700001700142856006000159 1995 eng d00aDoes cheating on CAT pay: Not0 aDoes cheating on CAT pay Not aSan Francisco1 aGershon, RC1 aBergstrom, B uhttp://mail.iacat.org/content/does-cheating-cat-pay-not00356nam a2200097 4500008004100000245004200041210004100083260004700124100001600171856007100187 1994 eng d00aCAT software system [computer program0 aCAT software system computer program aChicago IL: Computer Adaptive Technologies1 aGershon, RC uhttp://mail.iacat.org/content/cat-software-system-computer-program00369nas a2200133 4500008004100000245003000041210003000071300001200101490000600113100001400119700002400133700001600157856006200173 1994 eng d00aComputer adaptive testing0 aComputer adaptive testing a623-6340 v61 aLunz, M E1 aBergstrom, Betty, A1 aGershon, RC uhttp://mail.iacat.org/content/computer-adaptive-testing-100497nas a2200109 4500008004100000245010200041210006900143260001900212100001700231700001600248856012300264 1994 eng d00aComputerized adaptive testing exploring examinee response time using hierarchical linear modeling0 aComputerized adaptive testing exploring examinee response time u aNew Orleans LA1 aBergstrom, B1 aGershon, RC uhttp://mail.iacat.org/content/computerized-adaptive-testing-exploring-examinee-response-time-using-hierarchical-linear00453nas a2200121 4500008004100000245006600041210006600107300001000173490001600183100002400199700001600223856009200239 1994 eng d00aComputerized adaptive testing for licensure and certification0 aComputerized adaptive testing for licensure and certification a25-270 vWinter 19941 aBergstrom, Betty, A1 aGershon, RC uhttp://mail.iacat.org/content/computerized-adaptive-testing-licensure-and-certification00518nas a2200121 4500008004100000245008100041210006900122260004600191100001900237700001500256700002100271856010400292 1993 eng d00aIntroduction of a computer adaptive GRE General test (Research Report 93-57)0 aIntroduction of a computer adaptive GRE General test Research Re aPrinceton NJ: Educational Testing Service1 aSchaeffer, G A1 aSteffen, M1 aGolub-Smith, M L uhttp://mail.iacat.org/content/introduction-computer-adaptive-gre-general-test-research-report-93-5701221nas a2200157 4500008004100000245006600041210006600107300001200173490000600185520069800191653003400889100002400923700001400947700001600961856008600977 1992 eng d00aAltering the level of difficulty in computer adaptive testing0 aAltering the level of difficulty in computer adaptive testing a137-1490 v53 aExamines the effect of altering test difficulty on examinee ability measures and test length in a computer adaptive test. The 225 Ss were randomly assigned to 3 test difficulty conditions and given a variable length computer adaptive test. Examinees in the hard, medium, and easy test condition took a test targeted at the 50%, 60%, or 70% probability of correct response. The results show that altering the probability of a correct response does not affect estimation of examinee ability and that taking an easier computer adaptive test only slightly increases the number of items necessary to reach specified levels of precision. (PsycINFO Database Record (c) 2002 APA, all rights reserved).10acomputerized adaptive testing1 aBergstrom, Betty, A1 aLunz, M E1 aGershon, RC uhttp://mail.iacat.org/content/altering-level-difficulty-computer-adaptive-testing00442nas a2200109 4500008004100000245007300041210006900114260002100183100001700204700001600221856009500237 1992 eng d00aComparison of item targeting strategies for pass/fail adaptive tests0 aComparison of item targeting strategies for passfail adaptive te aSan Francisco CA1 aBergstrom, B1 aGershon, RC uhttp://mail.iacat.org/content/comparison-item-targeting-strategies-passfail-adaptive-tests00458nas a2200121 4500008004100000245006700041210006600108260002100174100001300195700001700208700001400225856009700239 1992 eng d00aStudent attitudes toward computer-adaptive test administration0 aStudent attitudes toward computeradaptive test administration aSan Francisco CA1 aBaghi, H1 aFerrara, S F1 aGabrys, R uhttp://mail.iacat.org/content/student-attitudes-toward-computer-adaptive-test-administration00417nas a2200121 4500008004100000245005800041210005700099260001500156100001300171700001400184700001500198856008200213 1991 eng d00aApplications of computer-adaptive testing in Maryland0 aApplications of computeradaptive testing in Maryland aChicago IL1 aBaghi, H1 aGabrys, R1 aFerrara, S uhttp://mail.iacat.org/content/applications-computer-adaptive-testing-maryland00536nas a2200133 4500008004100000245007400041210006900115260006600184100001500250700001400265700001600279700001300295856009400308 1991 eng d00aCollected works on the legal aspects of computerized adaptive testing0 aCollected works on the legal aspects of computerized adaptive te aChicago, IL: National Council of State Boards of Nursing, Inc1 aStenson, H1 aGraves, P1 aGardiner, J1 aDally, L uhttp://mail.iacat.org/content/collected-works-legal-aspects-computerized-adaptive-testing00491nas a2200109 4500008004100000245010800041210006900149260001500218100001300233700001500246856012000261 1991 eng d00aDevelopment and evaluation of hierarchical testlets in two-stage tests using integer linear programming0 aDevelopment and evaluation of hierarchical testlets in twostage  aChicago IL1 aLam, T L1 aGoong, Y Y uhttp://mail.iacat.org/content/development-and-evaluation-hierarchical-testlets-two-stage-tests-using-integer-linear00469nas a2200097 4500008004100000245010200041210006900143100001600212700001700228856012600245 1991 eng d00aIndividual differences in computer adaptive testing: Anxiety, computer literacy, and satisfaction0 aIndividual differences in computer adaptive testing Anxiety comp1 aGershon, RC1 aBergstrom, B uhttp://mail.iacat.org/content/individual-differences-computer-adaptive-testing-anxiety-computer-literacy-and-satisfaction00516nam 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-challenges00437nas a2200121 4500008004100000245005600041210005400097260002800151100001400179700002400193700001600217856008200233 1990 eng d00aTest-retest consistency of computer adaptive tests.0 aTestretest consistency of computer adaptive tests aBoston, MA USAc04/19901 aLunz, M E1 aBergstrom, Betty, A1 aGershon, RC uhttp://mail.iacat.org/content/test-retest-consistency-computer-adaptive-tests00553nas a2200109 4500008004100000245011200041210006900153260006900222100001400291700001600305856012200321 1990 eng d00aUtility of predicting starting abilities in sequential computer-based adaptive tests (Research Report 90-1)0 aUtility of predicting starting abilities in sequential computerb aBaltimore MD: Johns Hopkins University, Department of Psychology1 aGreen, BF1 aThomas, T J uhttp://mail.iacat.org/content/utility-predicting-starting-abilities-sequential-computer-based-adaptive-tests-research00456nas a2200121 4500008004100000245008100041210006900122300001200191490000700203100000900210700001400219856010100233 1989 eng d00aAdaptive estimation when the unidimensionality assumption of IRT is violated0 aAdaptive estimation when the unidimensionality assumption of IRT a373-3890 v131 aFolk1 aGreen, BF uhttp://mail.iacat.org/content/adaptive-estimation-when-unidimensionality-assumption-irt-violated00467nas a2200121 4500008004500000245008100045210006900126300001200195490000700207100001400214700001400228856010300242 1989 Engldsh 00aAdaptive Estimation When the Unidimensionality Assumption of IRT is Violated0 aAdaptive Estimation When the Unidimensionality Assumption of IRT a373-3900 v131 aFolk, V G1 aGreen, BF uhttp://mail.iacat.org/content/adaptive-estimation-when-unidimensionality-assumption-irt-violated-000335nam a2200097 4500008004100000245004100041210003900082260003100121100001600152856006900168 1989 eng d00aCAT administrator [Computer program]0 aCAT administrator Computer program aChicago: Micro Connections1 aGershon, RC uhttp://mail.iacat.org/content/cat-administrator-computer-program00397nas 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-tests00590nas a2200109 4500008004100000245012200041210006900163260009400232100001600326700001400342856012400356 1989 eng d00aItem-presentation controls for computerized adaptive testing: Content-balancing versus min-CAT (Research Report 89-1)0 aItempresentation controls for computerized adaptive testing Cont aBaltimore MD: Johns Hopkins University, Department of Psychology, Psychometric Laboratory1 aThomas, T J1 aGreen, BF uhttp://mail.iacat.org/content/item-presentation-controls-computerized-adaptive-testing-content-balancing-versus-min-cat00406nas a2200097 4500008004100000245004700041210004600088260008600134100001400220856007400234 1988 eng d00aConstruct validity of computer-based tests0 aConstruct validity of computerbased tests aH. Wainer and H. Braun (Eds.), Test validity (pp. 77-103). Hillsdale NJ: Erlbaum.1 aGreen, BF uhttp://mail.iacat.org/content/construct-validity-computer-based-tests00412nas a2200109 4500008004100000245007100041210006500112300001200177490000600189100001400195856009300209 1988 eng d00aCritical problems in computer-based psychological measurement, , ,0 aCritical problems in computerbased psychological measurement a223-2310 v11 aGreen, BF uhttp://mail.iacat.org/content/critical-problems-computer-based-psychological-measurement01300nas a2200109 4500008004100000245007900041210006900120260003600189520085200225100002001077856009301097 1988 eng d00aThe Rasch model and missing data, with an emphasis on tailoring test items0 aRasch model and missing data with an emphasis on tailoring test  aNew Orleans, LA. USAcApril 5-93 aMany applications of educational testing have a missing data aspect (MDA). This MDA is perhaps most pronounced in item banking, where each examinee responds to a different subtest of items from a large item pool and where both person and item parameter estimates are needed. The Rasch model is emphasized, and its non-parametric counterpart (the Mokken scale) is considered. The possibility of tailoring test items in combination with their estimation is discussed; however, most methods for the estimation of item parameters are inadequate under tailoring. Without special measures, only marginal maximum likelihood produces adequate item parameter estimates under item tailoring. Fischer's approximate minimum-chi-square method for estimation of item parameters for the Rasch model is discussed, which efficiently produces item parameters. (TJH)1 aGruijter, D N M uhttp://mail.iacat.org/content/rasch-model-and-missing-data-emphasis-tailoring-test-items00337nas a2200109 4500008004100000245004400041210003900085300001000124490000700134100001600141856007000157 1988 eng d00aThe Rasch model and multi-stage testing0 aRasch model and multistage testing a45-520 v131 aGlas, C A W uhttp://mail.iacat.org/content/rasch-model-and-multi-stage-testing00432nas a2200109 4500008004100000245007500041210006900116300000900185490000900194100001800203856010100221 1987 eng d00aWilcox' closed sequential testing procedure in stratified item domains0 aWilcox closed sequential testing procedure in stratified item do a3-120 v1(1)1 aGruijter, D N uhttp://mail.iacat.org/content/wilcox-closed-sequential-testing-procedure-stratified-item-domains01525nas a2200157 4500008004100000020001400041245008900055210006900144300001000213490000700223520095700230653003401187100001801221700002001239856010801259 1986 eng d a0013-164400aAn application of computer adaptive testing with communication handicapped examinees0 aapplication of computer adaptive testing with communication hand a23-350 v463 aThis study was conducted to evaluate a computerized adaptive testing procedure for the measurement of mathematical skills of entry level deaf college students. The theoretical basis of the study was the Rasch model for person measurement. Sixty persons were tested using an Apple II Plus microcomputer. Ability estimates provided by the computerized procedure were compared for stability with those obtained six to eight weeks earlier from conventional (written) testing of the same subject matter. Students' attitudes toward their testing experiences also were measured. Substantial increases in measurement efficiency (by reducing test length) were realized through the adaptive testing procedure. Because the item pool used was not specifically designed for adaptive testing purposes, the psychometric quality of measurements resulting from the different testing methods was approximately equal. Attitudes toward computerized testing were favorable.10acomputerized adaptive testing1 aGarrison, W M1 aBaumgarten, B S uhttp://mail.iacat.org/content/application-computer-adaptive-testing-communication-handicapped-examinees00444nas a2200121 4500008004100000245007300041210006900114300001000183490000700193100001100200700001400211856009700225 1986 eng d00aEquivalence of conventional and computer presentation of speed tests0 aEquivalence of conventional and computer presentation of speed t a23-340 v101 aGreaud1 aGreen, BF uhttp://mail.iacat.org/content/equivalence-conventional-and-computer-presentation-speed-tests00483nas a2200109 4500008004100000245009200041210006900133260002100202100001400223700001700237856011900254 1986 eng d00aOperational characteristics of adaptive testing procedures using partial credit scoring0 aOperational characteristics of adaptive testing procedures using aSan Francisco CA1 aKoch, W R1 aG., Dodd., B uhttp://mail.iacat.org/content/operational-characteristics-adaptive-testing-procedures-using-partial-credit-scoring00441nas a2200109 4500008004100000245008400041210006900125300000900194490000700203100001800210856010300228 1985 eng d00aMonitoring item calibrations from data yielded by an adaptive testing procedure0 aMonitoring item calibrations from data yielded by an adaptive te a9-120 v101 aGarrison, W M uhttp://mail.iacat.org/content/monitoring-item-calibrations-data-yielded-adaptive-testing-procedure00407nas a2200109 4500008003900000245004400039210004400083260006900127100001600196700001400212856007100226 1984 d00aAnalysis of experimental CAT ASVAB data0 aAnalysis of experimental CAT ASVAB data aBaltimore MD: Johns Hopkins University, Department of Psychology1 aAllred, L A1 aGreen, BF uhttp://mail.iacat.org/content/analysis-experimental-cat-asvab-data00456nas a2200109 4500008004100000245006300041210006300104260006900167100001100236700001400247856008500261 1984 eng d00aAnalysis of speeded test data from experimental CAT system0 aAnalysis of speeded test data from experimental CAT system aBaltimore MD: Johns Hopkins University, Department of Psychology1 aGreaud1 aGreen, BF uhttp://mail.iacat.org/content/analysis-speeded-test-data-experimental-cat-system00543nas a2200133 4500008004100000245010100041210006900142100001400211700001400225700001900239700001300258700001700271856012100288 1984 eng d00aEvaluation plan for the computerized adaptive vocational aptitude battery (Research Report 82-1)0 aEvaluation plan for the computerized adaptive vocational aptitud1 aGreen, BF1 aBock, R D1 aHumphreys, L G1 aLinn, RL1 aReckase, M D uhttp://mail.iacat.org/content/evaluation-plan-computerized-adaptive-vocational-aptitude-battery-research-report-82-100557nas a2200157 4500008004100000245009200041210006900133300001200202490000700214100001400221700000900235700001300244700001300257700001700270856011200287 1984 eng d00aA plan for scaling the computerized adaptive Armed Services Vocational Aptitude Battery0 aplan for scaling the computerized adaptive Armed Services Vocati a347-3600 v211 aGreen, BF1 aBock1 aLinn, RL1 aLord, FM1 aReckase, M D uhttp://mail.iacat.org/content/plan-scaling-computerized-adaptive-armed-services-vocational-aptitude-battery00656nas a2200205 4500008004100000020001400041245006700055210006700122300001200189490000700201653003400208653001700242653002100259100001400280700001400294700001900308700001300327700001700340856009300357 1984 eng d a1745-398400aTechnical guidelines for assessing computerized adaptive tests0 aTechnical guidelines for assessing computerized adaptive tests a347-3600 v2110acomputerized adaptive testing10aMode effects10apaper-and-pencil1 aGreen, BF1 aBock, R D1 aHumphreys, L G1 aLinn, RL1 aReckase, M D uhttp://mail.iacat.org/content/technical-guidelines-assessing-computerized-adaptive-tests00446nas a2200097 4500008004100000245003300041210003300074260016500107100001400272856006200286 1983 eng d00aAdaptive testing by computer0 aAdaptive testing by computer aR. B. Ekstrom (ed.), Measurement, technology, and individuality in education. New directions for testing and measurement, Number 17. San Francisco: Jossey-Bass.1 aGreen, BF uhttp://mail.iacat.org/content/adaptive-testing-computer-000452nas a2200121 4500008004100000245007800041210006900119300001000188490000700198100001500205700001400220856009600234 1983 eng d00aAn application of computerized adaptive testing in U. S. Army recruiting.0 aapplication of computerized adaptive testing in U S Army recruit a87-890 v101 aSands, W A1 aGade, P A uhttp://mail.iacat.org/content/application-computerized-adaptive-testing-u-s-army-recruiting00394nas a2200097 4500008004100000245003400041210003000075260012000105100001400225856005700239 1983 eng d00aThe promise of tailored tests0 apromise of tailored tests aH. Wainer and S. Messick (Eds.). Principals of modern psychological measurement (pp. 69-80). Hillsdale NJ: Erlbaum.1 aGreen, BF uhttp://mail.iacat.org/content/promise-tailored-tests00434nas a2200109 4500008004100000245007000041210006900111260001300180100001800193700002000211856009300231 1982 eng d00aAssessing mathematics achievement with a tailored testing program0 aAssessing mathematics achievement with a tailored testing progra aNew York1 aGarrison, W M1 aBaumgarten, B S uhttp://mail.iacat.org/content/assessing-mathematics-achievement-tailored-testing-program00489nam a2200097 4500008004100000245008400041210006900125260007400194100001400268856010900282 1980 eng d00aA comparative evaluation of two Bayesian adaptive ability estimation procedures0 acomparative evaluation of two Bayesian adaptive ability estimati aUnpublished doctoral dissertation, the Catholic University of America1 aGorman, S uhttp://mail.iacat.org/content/comparative-evaluation-two-bayesian-adaptive-ability-estimation-procedures00539nas a2200109 4500008004100000245011800041210006900159260005000228490001000278100001400288856012700302 1980 eng d00aA comparative evaluation of two Bayesian adaptive ability estimation procedures with a conventional test strategy0 acomparative evaluation of two Bayesian adaptive ability estimati aWashington DCbCatholic University of America0 vPh.D.1 aGorman, S uhttp://mail.iacat.org/content/comparative-evaluation-two-bayesian-adaptive-ability-estimation-procedures-conventional-test00654nas a2200097 4500008004100000245010500041210006900146260021000215100001400425856011700439 1980 eng d00aA comparison of the accuracy of Bayesian adaptive and static tests using a correction for regression0 acomparison of the accuracy of Bayesian adaptive and static tests aD. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 35-50). Minneapolis MN: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory.1 aGorman, S uhttp://mail.iacat.org/content/comparison-accuracy-bayesian-adaptive-and-static-tests-using-correction-regression00617nas 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-79-200598nas 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-achievement00486nas a2200133 4500008004100000245007400041210006900115300001200184490000700196100001700203700001400220700001500234856010300249 1978 eng d00aComputer-assisted tailored testing: Examinee reactions and evaluation0 aComputerassisted tailored testing Examinee reactions and evaluat a265-2730 v381 aSchmidt, F L1 aUrry, V W1 aGugel, J F uhttp://mail.iacat.org/content/computer-assisted-tailored-testing-examinee-reactions-and-evaluation00573nas a2200121 4500008004100000245008700041210006900128260009400197100001700291700001400308700001500322856011400337 1977 eng d00aComputer-assisted tailored testing: Examinee reactions and evaluation (PB-276 748)0 aComputerassisted tailored testing Examinee reactions and evaluat aWashington DC: U. S. Civil Service Commission, Personnel Research and Development Center.1 aSchmidt, F L1 aUrry, V W1 aGugel, J F uhttp://mail.iacat.org/content/computer-assisted-tailored-testing-examinee-reactions-and-evaluation-pb-276-74800542nas a2200097 4500008003900000245006100039210006100100260018500161100001400346856008400360 1977 d00aComputerized Adaptive Testing with a Military Population0 aComputerized Adaptive Testing with a Military Population aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolls MN: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aGorman, S uhttp://mail.iacat.org/content/computerized-adaptive-testing-military-population00606nas 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-achievement00412nas a2200097 4500008004100000245005400041210004800095260007100143100002000214856008000234 1977 eng d00aA two-stage testing procedure (Memorandum 403-77)0 atwostage testing procedure Memorandum 40377 aUniversity of Leyden, The Netherlands, Educational Research Center1 aGruijter, D N M uhttp://mail.iacat.org/content/two-stage-testing-procedure-memorandum-403-7700389nas a2200097 4500008004100000245001500041210001500056260015900071100001400230856004700244 1976 eng d00aDiscussion0 aDiscussion aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. pp. 118-119). Washington DC: U.S. Government Printing Office.1 aGreen, BF uhttp://mail.iacat.org/content/discussion-000555nas a2200121 4500008004100000245005600041210005600097260015500153100001500308700001700323700001400340856007900354 1976 eng d00aEffectiveness of the ancillary estimation procedure0 aEffectiveness of the ancillary estimation procedure aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 103-106). Washington DC: U.S. Government Printing Office.1 aGugel, J F1 aSchmidt, F L1 aUrry, V W uhttp://mail.iacat.org/content/effectiveness-ancillary-estimation-procedure00505nas a2200097 4500008004100000245002000041210002000061260026000081100001600341856005000357 1976 eng d00aOpening remarks0 aOpening remarks aW. H. Gorham (Chair), Computers and testing: Steps toward the inevitable conquest (PS 76-1). Symposium presented at the 83rd annual convention of the APA, Chicago IL. Washington DC: U.S. Civil Service Commission, Personnel Research and Developement Center1 aGorham, W A uhttp://mail.iacat.org/content/opening-remarks00486nas a2200121 4500008004100000245009300041210006900134300000900203490000700212100001600219700001700235856011200252 1972 eng d00aIndividual intelligence testing without the examiner: reliability of an automated method0 aIndividual intelligence testing without the examiner reliability a9-140 v381 aElwood, D L1 aGriffin, H R uhttp://mail.iacat.org/content/individual-intelligence-testing-without-examiner-reliability-automated-method00400nas a2200097 4500008004100000245003300041210003300074260012100107100001400228856006000242 1970 eng d00aComments on tailored testing0 aComments on tailored testing aW. H. Holtzman, (Ed.), Computer-assisted instruction, testing, and guidance (pp. 184-197). New York: Harper and Row.1 aGreen, BF uhttp://mail.iacat.org/content/comments-tailored-testing00371nas a2200121 4500008004100000245004400041210004400085300001200129490000700141100001900148700001400167856006800181 1965 eng d00aAdaptive testing in an older population0 aAdaptive testing in an older population a193-1980 v601 aGreenwood, D I1 aTaylor, C uhttp://mail.iacat.org/content/adaptive-testing-older-population