@inbook {2050,
	title = {Constrained Adaptive Testing with Shadow Tests},
	booktitle = {Elements of Adaptive Testing},
	year = {2010},
	pages = {31-56},
	chapter = {2},
	doi = {10.1007/978-0-387-85461-8},
	author = {van der Linden, W. J.}
}
@inbook {2060,
	title = {Designing Item Pools for Adaptive Testing},
	booktitle = {Elements of Adaptive Testing},
	year = {2010},
	pages = {231-245},
	chapter = {12},
	doi = {10.1007/978-0-387-85461-8},
	author = {Veldkamp, B. P. and van der Linden, W. J.}
}
@book {2048,
	title = {Elements of Adaptive Testing},
	year = {2010},
	pages = {437},
	publisher = {Springer},
	organization = {Springer},
	address = {New York},
	doi = {10.1007/978-0-387-85461-8},
	author = {van der Linden, W. J. and Glas, C. A. W.}
}
@inbook {2063,
	title = {Estimation of the Parameters in an Item-Cloning Model for Adaptive Testing},
	booktitle = {Elements of Adaptive Testing},
	year = {2010},
	pages = {289-314},
	chapter = {15},
	doi = {10.1007/978-0-387-85461-8 },
	author = {Glas, C. A. W. and van der Linden, W. J. and Geerlings, H.}
}
@inbook {2049,
	title = {Item Selection and Ability Estimation in Adaptive Testing},
	booktitle = {Elements of Adaptive Testing},
	year = {2010},
	pages = {3-30},
	publisher = {Springer},
	organization = {Springer},
	chapter = {1},
	address = {New York},
	doi = {10.1007/978-0-387-85461-8},
	author = {van der Linden, W. J. and Pashley, P. J.}
}
@article {157,
	title = {Marginal likelihood inference for a model for item responses and response times},
	journal = {British Journal of Mathematical and Statistical Psychology},
	volume = {63},
	number = {3},
	year = {2010},
	note = {Glas, Cees A Wvan der Linden, Wim JResearch Support, Non-U.S. Gov{\textquoteright}tEnglandThe British journal of mathematical and statistical psychologyBr J Math Stat Psychol. 2010 Nov;63(Pt 3):603-26. Epub 2010 Jan 28.},
	pages = {603-26},
	edition = {2010/01/30},
	abstract = {<p>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\&$\#$39;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.</p>
},
	isbn = {0007-1102 (Print)0007-1102 (Linking)},
	author = {Glas, C. A. W. and van der Linden, W. J.}
}
@inbook {2052,
	title = {Multidimensional Adaptive Testing with Kullback{\textendash}Leibler Information Item Selection},
	booktitle = {Elements of Adaptive Testing},
	year = {2010},
	pages = {77-102},
	chapter = {4},
	doi = {10.1007/978-0-387-85461-8},
	author = {Mulder, J. and van der Linden, W. J.}
}
@inbook {2053,
	title = {Sequencing an Adaptive Test Battery},
	booktitle = {Elements of Adaptive Testing},
	year = {2010},
	chapter = {5},
	doi = {10.1007/978-0-387-85461-8},
	author = {van der Linden, W. J.}
}
@article {288,
	title = {Multidimensional Adaptive Testing with Optimal Design Criteria for Item Selection},
	journal = {Psychometrika},
	volume = {74},
	number = {2},
	year = {2009},
	note = {Journal articlePsychometrikaPsychometrika. 2009 Jun;74(2):273-296. Epub 2008 Dec 23.},
	month = {Jun},
	pages = {273-296},
	edition = {2010/02/02},
	abstract = {Several criteria from the optimal design literature are examined for use with item selection in multidimensional adaptive testing. In particular, it is examined what criteria are appropriate for adaptive testing in which all abilities are intentional, some should be considered as a nuisance, or the interest is in the testing of a composite of the abilities. Both the theoretical analyses and the studies of simulated data in this paper suggest that the criteria of A-optimality and D-optimality lead to the most accurate estimates when all abilities are intentional, with the former slightly outperforming the latter. The criterion of E-optimality showed occasional erratic behavior for this case of adaptive testing, and its use is not recommended. If some of the abilities are nuisances, application of the criterion of A(s)-optimality (or D(s)-optimality), which focuses on the subset of intentional abilities is recommended. For the measurement of a linear combination of abilities, the criterion of c-optimality yielded the best results. The preferences of each of these criteria for items with specific patterns of parameter values was also assessed. It was found that the criteria differed mainly in their preferences of items with different patterns of values for their discrimination parameters.},
	isbn = {0033-3123 (Print)0033-3123 (Linking)},
	author = {Mulder, J. and van der Linden, W. J.}
}
@article {742,
	title = {Adaptive models of psychological testing},
	journal = {Zeitschrift f{\"u}r Psychologie / Journal of Psychology},
	volume = {216(1)},
	year = {2008},
	pages = {3{\textendash}11},
	author = {van der Linden, W. J.}
}
@article {2104,
	title = {Adaptive Models of Psychological Testing},
	journal = {Zeitschrift f{\"u}r Psychologie / Journal of Psychology},
	volume = {216},
	year = {2008},
	pages = {1-2},
	doi = {10.1027/0044-3409.216.1.49},
	author = {van der Linden, W. J.}
}
@article {400,
	title = {Some new developments in adaptive testing technology},
	journal = {Zeitschrift f{\"u}r Psychologie},
	volume = {216},
	number = {1},
	year = {2008},
	pages = {3-11},
	abstract = {<p>In an ironic twist of history, modern psychological testing has returned to an adaptive format quite common when testing was not yet standardized. Important stimuli to the renewed interest in adaptive testing have been the development of item-response theory in psychometrics, which models the responses on test items using separate parameters for the items and test takers, and the use of computers in test administration, which enables us to estimate the parameter for a test taker and select the items in real time. This article reviews a selection from the latest developments in the technology of adaptive testing, such as constrained adaptive item selection, adaptive testing using rule-based item generation, multidimensional adaptive testing, adaptive use of test batteries, and the use of response times in adaptive testing.</p>
},
	keywords = {computerized adaptive testing},
	author = {van der Linden, W. J.}
}
@article {743,
	title = {Using response times for item selection in adaptive testing},
	journal = {Journal of Educational and Behavioral Statistics},
	volume = {33},
	year = {2008},
	pages = {5{\textendash}20},
	author = {van der Linden, W. J.}
}
@inbook {1924,
	title = {The shadow-test approach: A universal framework for implementing adaptive testing},
	year = {2007},
	note = {{PDF file, 461 KB}},
	address = {D. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.},
	author = {van der Linden, W. J.}
}
@inbook {1926,
	title = {Statistical aspects of adaptive testing},
	year = {2007},
	address = {C. R. Rao and S. Sinharay (Eds.), Handbook of statistics (Vol. 27: Psychometrics) (pp. 801838). Amsterdam: North-Holland.},
	author = {van der Linden, W. J. and Glas, C. A. W.}
}
@article {401,
	title = {Assembling a computerized adaptive testing item pool as a set of linear tests},
	journal = {Journal of Educational and Behavioral Statistics},
	volume = {31},
	number = {1},
	year = {2006},
	pages = {81-99},
	publisher = {Sage Publications: US},
	abstract = {Test-item writing efforts typically results in item pools with an undesirable correlational structure between the content attributes of the items and their statistical information. If such pools are used in computerized adaptive testing (CAT), the algorithm may be forced to select items with less than optimal information, that violate the content constraints, and/or have unfavorable exposure rates. Although at first sight somewhat counterintuitive, it is shown that if the CAT pool is assembled as a set of linear test forms, undesirable correlations can be broken down effectively. It is proposed to assemble such pools using a mixed integer programming model with constraints that guarantee that each test meets all content specifications and an objective function that requires them to have maximal information at a well-chosen set of ability values. An empirical example with a previous master pool from the Law School Admission Test (LSAT) yielded a CAT with nearly uniform bias and mean-squared error functions for the ability estimator and item-exposure rates that satisfied the target for all items in the pool. },
	keywords = {Algorithms, computerized adaptive testing, item pool, linear tests, mathematical models, statistics, Test Construction, Test Items},
	isbn = {1076-9986 (Print)},
	author = {van der Linden, W. J. and Ariel, A. and Veldkamp, B. P.}
}
@article {399,
	title = {Equating scores from adaptive to linear tests},
	journal = {Applied Psychological Measurement},
	volume = {30},
	number = {6},
	year = {2006},
	pages = {493-508},
	publisher = {Sage Publications: US},
	abstract = {Two local methods for observed-score equating are applied to the problem of equating an adaptive test to a linear test. In an empirical study, the methods were evaluated against a method based on the test characteristic function (TCF) of the linear test and traditional equipercentile equating applied to the ability estimates on the adaptive test for a population of test takers. The two local methods were generally best. Surprisingly, the TCF method performed slightly worse than the equipercentile method. Both methods showed strong bias and uniformly large inaccuracy, but the TCF method suffered from extra error due to the lower asymptote of the test characteristic function. It is argued that the worse performances of the two methods are a consequence of the fact that they use a single equating transformation for an entire population of test takers and therefore have to compromise between the individual score distributions. },
	keywords = {computerized adaptive testing, equipercentile equating, local equating, score reporting, test characteristic function},
	isbn = {0146-6216 (Print)},
	author = {van der Linden, W. J.}
}
@article {741,
	title = {A comparison of item-selection methods for adaptive tests with content constraints},
	journal = {Journal of Educational Measurement},
	volume = {42},
	year = {2005},
	pages = {283-302},
	author = {van der Linden, W. J.}
}
@article {398,
	title = {A comparison of item-selection methods for adaptive tests with content constraints},
	journal = {Journal of Educational Measurement},
	volume = {42},
	number = {3},
	year = {2005},
	pages = {283-302},
	publisher = {Blackwell Publishing: United Kingdom},
	abstract = {In test assembly, a fundamental difference exists between algorithms that select a test sequentially or simultaneously. Sequential assembly allows us to optimize an objective function at the examinee{\textquoteright}s ability estimate, such as the test information function in computerized adaptive testing. But it leads to the non-trivial problem of how to realize a set of content constraints on the test{\textemdash}a problem more naturally solved by a simultaneous item-selection method. Three main item-selection methods in adaptive testing offer solutions to this dilemma. The spiraling method moves item selection across categories of items in the pool proportionally to the numbers needed from them. Item selection by the weighted-deviations method (WDM) and the shadow test approach (STA) is based on projections of the future consequences of selecting an item. These two methods differ in that the former calculates a projection of a weighted sum of the attributes of the eventual test and the latter a projection of the test itself. The pros and cons of these methods are analyzed. An empirical comparison between the WDM and STA was conducted for an adaptive version of the Law School Admission Test (LSAT), which showed equally good item-exposure rates but violations of some of the constraints and larger bias and inaccuracy of the ability estimator for the WDM.},
	keywords = {Adaptive Testing, Algorithms, content constraints, item selection method, shadow test approach, spiraling method, weighted deviations method},
	isbn = {0022-0655 (Print)},
	author = {van der Linden, W. J.}
}
@booklet {1540,
	title = {Constraining item exposure in computerized adaptive testing with shadow tests},
	year = {2005},
	address = {Law School Admission Council Computerized Testing Report 02-03},
	author = {van der Linden, W. J. and Veldkamp, B. P.}
}
@booklet {1534,
	title = {Implementing content constraints in alpha-stratified adaptive testing using a shadow test approach},
	year = {2005},
	address = {Law School Admission Council, Computerized Testing Report 01-09},
	author = {van der Linden, W. J. and Chang, Hua-Hua}
}
@article {408,
	title = {Constraining item exposure in computerized adaptive testing with shadow tests},
	journal = {Journal of Educational and Behavioral Statistics},
	volume = {29},
	number = {3},
	year = {2004},
	pages = {273-291},
	publisher = {American Educational Research Assn: US},
	abstract = {Item-exposure control in computerized adaptive testing is implemented by imposing item-ineligibility constraints on the assembly process of the shadow tests. The method resembles Sympson and Hetter{\textquoteright}s (1985) method of item-exposure control in that the decisions to impose the constraints are probabilistic. The method does not, however, require time-consuming simulation studies to set values for control parameters before the operational use of the test. Instead, it can set the probabilities of item ineligibility adaptively during the test using the actual item-exposure rates. An empirical study using an item pool from the Law School Admission Test showed that application of the method yielded perfect control of the item-exposure rates and had negligible impact on the bias and mean-squared error functions of the ability estimator. },
	keywords = {computerized adaptive testing, item exposure control, item ineligibility constraints, Probability, shadow tests},
	isbn = {1076-9986 (Print)},
	author = {van der Linden, W. J. and Veldkamp, B. P.}
}
@article {10,
	title = {Constructing rotating item pools for constrained adaptive testing},
	journal = {Journal of Educational Measurement},
	volume = {41},
	number = {4},
	year = {2004},
	pages = {345-359},
	publisher = {Blackwell Publishing: United Kingdom},
	abstract = {Preventing items in adaptive testing from being over- or underexposed is one of the main problems in computerized adaptive testing. Though the problem of overexposed items can be solved using a probabilistic item-exposure control method, such methods are unable to deal with the problem of underexposed items. Using a system of rotating item pools, on the other hand, is a method that potentially solves both problems. In this method, a master pool is divided into (possibly overlapping) smaller item pools, which are required to have similar distributions of content and statistical attributes. These pools are rotated among the testing sites to realize desirable exposure rates for the items. A test assembly model, motivated by Gulliksen{\textquoteright}s matched random subtests method, was explored to help solve the problem of dividing a master pool into a set of smaller pools. Different methods to solve the model are proposed. An item pool from the Law School Admission Test was used to evaluate the performances of computerized adaptive tests from systems of rotating item pools constructed using these methods. (PsycINFO Database Record (c) 2007 APA, all rights reserved)},
	keywords = {computerized adaptive tests, constrained adaptive testing, item exposure, rotating item pools},
	isbn = {0022-0655 (Print)},
	author = {Ariel, A. and Veldkamp, B. P. and van der Linden, W. J.}
}
@conference {1211,
	title = {A sequential Bayesian procedure for item calibration in multistage testing},
	booktitle = {Paper presented at the annual meeting of the National Council on Measurement in Education},
	year = {2004},
	address = {San Diego CA},
	author = {van der Linden, W. J. and Alan D Mead}
}
@article {744,
	title = {Alpha-stratified adaptive testing with large numbers of content constraints},
	journal = {Applied Psychological Measurement},
	volume = {27},
	year = {2003},
	pages = {107-120},
	author = {van der Linden, W. J. and Chang, Hua-Hua}
}
@inbook {1923,
	title = {Bayesian checks on outlying response times in computerized adaptive testing},
	year = {2003},
	address = {H. Yanai, A. Okada, K. Shigemasu, Y. Kano, Y. and J. J. Meulman, (Eds.), New developments in psychometrics (pp. 215-222). New York: Springer-Verlag.},
	author = {van der Linden, W. J.}
}
@article {156,
	title = {Computerized adaptive testing with item cloning},
	journal = {Applied Psychological Measurement},
	volume = {27},
	number = {4},
	year = {2003},
	note = {References .Sage Publications, US},
	pages = {247-261},
	abstract = {(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).},
	keywords = {computerized adaptive testing},
	author = {Glas, C. A. W. and van der Linden, W. J.}
}
@conference {1213,
	title = {Constraining item exposure in computerized adaptive testing with shadow tests},
	booktitle = {Paper presented at the Annual meeting of the National Council on Measurement in Education},
	year = {2003},
	note = {$\#$vdLI03-02},
	address = {Chicago IL},
	author = {van der Linden, W. J. and Veldkamp, B. P.}
}
@conference {829,
	title = {Constructing rotating item pools for constrained adaptive testing},
	booktitle = {Paper presented at the Annual meeting of the National Council on Measurement in Education},
	year = {2003},
	note = {{PDF file, 395 KB}},
	address = {Chicago IL},
	author = {Ariel, A. and Veldkamp, B. and van der Linden, W. J.}
}
@conference {1215,
	title = {Controlling item exposure and item eligibility in computerized adaptive testing},
	year = {2003},
	author = {van der Linden, W. J. and Veldkamp, B. P.}
}
@conference {1216,
	title = {Implementing an alternative to Sympson-Hetter item-exposure control in constrained adaptive testing},
	booktitle = {Paper presented at the Annual meeting of the National Council on Measurement in Education},
	year = {2003},
	address = {Chicago IL},
	author = {Veldkamp, B. P. and van der Linden, W. J.}
}
@article {745,
	title = {Implementing content constraints in alpha-stratified adaptive testing using a shadow test approach},
	journal = {Applied Psychological Measurement},
	volume = {27},
	year = {2003},
	pages = {107-120},
	author = {van der Linden, W. J. and Chang, Hua-Hua}
}
@article {57,
	title = {Optimal stratification of item pools in α-stratified computerized adaptive testing},
	journal = {Applied Psychological Measurement},
	volume = {27},
	number = {4},
	year = {2003},
	pages = {262-274},
	abstract = {A method based on 0-1 linear programming (LP) is presented to stratify an item pool optimally for use in α-stratified adaptive testing. Because the 0-1 LP model belongs to the subclass of models with a network flow structure, efficient solutions are possible. The method is applied to a previous item pool from the computerized adaptive testing (CAT) version of the Graduate Record Exams (GRE) Quantitative Test. The results indicate that the new method performs well in practical situations. It improves item exposure control, reduces the mean squared error in the θ estimates, and increases test reliability. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)},
	keywords = {Adaptive Testing, Computer Assisted Testing, Item Content (Test), Item Response Theory, Mathematical Modeling, Test Construction computerized adaptive testing},
	author = {Chang, Hua-Hua and van der Linden, W. J.}
}
@booklet {1536,
	title = {A sequential Bayes procedure for item calibration in multi-stage testing},
	year = {2003},
	address = {Manuscript in preparation},
	author = {van der Linden, W. J. and Alan D Mead}
}
@article {397,
	title = {Some alternatives to Sympson-Hetter item-exposure control in computerized adaptive testing},
	journal = {Journal of Educational and Behavioral Statistics},
	volume = {28},
	number = {3},
	year = {2003},
	pages = {249-265},
	abstract = {TheHetter and Sympson (1997; 1985) method is a method of probabilistic item-exposure control in computerized adaptive testing. Setting its control parameters to admissible values requires an iterative process of computer simulations that has been found to be time consuming, particularly if the parameters have to be set conditional on a realistic set of values for the examinees{\textquoteright} ability parameter. Formal properties of the method are identified that help us explain why this iterative process can be slow and does not guarantee admissibility. In addition, some alternatives to the SH method are introduced. The behavior of these alternatives was estimated for an adaptive test from an item pool from the Law School Admission Test (LSAT). Two of the alternatives showed attractive behavior and converged smoothly to admissibility for all items in a relatively small number of iteration steps. },
	keywords = {Adaptive Testing, Computer Assisted Testing, Test Items computerized adaptive testing},
	author = {van der Linden, W. J.}
}
@article {407,
	title = {Using response times to detect aberrant responses in computerized adaptive testing},
	journal = {Psychometrika},
	volume = {68},
	number = {2},
	year = {2003},
	pages = {251-265},
	abstract = {A lognormal model for response times is used to check response times for aberrances in examinee behavior on computerized adaptive tests. Both classical procedures and Bayesian posterior predictive checks are presented. For a fixed examinee, responses and response times are independent; checks based on response times offer thus information independent of the results of checks on response patterns. Empirical examples of the use of classical and Bayesian checks for detecting two different types of aberrances in response times are presented. The detection rates for the Bayesian checks outperformed those for the classical checks, but at the cost of higher false-alarm rates. A guideline for the choice between the two types of checks is offered.},
	keywords = {Adaptive Testing, Behavior, Computer Assisted Testing, computerized adaptive testing, Models, person Fit, Prediction, Reaction Time},
	author = {van der Linden, W. J. and van Krimpen-Stoop, E. M. L. A.}
}
@booklet {1539,
	title = {Constraining item exposure in computerized adaptive testing with shadow tests (Research Report No. 02-06)},
	year = {2002},
	address = {University of Twente, The Netherlands},
	author = {van der Linden, W. J. and Veldkamp, B. P.}
}
@article {418,
	title = {Mathematical-programming approaches to test item pool design},
	number = {RR 02-09},
	year = {2002},
	note = {Using Smart Source ParsingAdvances in psychology research, Vol. ( Hauppauge, NY : Nova Science Publishers, Inc, [URL:http://www.Novapublishers.com]. vi, 228 pp},
	pages = {93-108},
	institution = {University of Twente, Faculty of Educational Science and Technology},
	address = {Twente, The Netherlands},
	abstract = {(From the chapter) This paper presents an approach to item pool design that has the potential to improve on the quality of current item pools in educational and psychological testing and hence to increase both measurement precision and validity. The approach consists of the application of mathematical programming techniques to calculate optimal blueprints for item pools. These blueprints can be used to guide the item-writing process. Three different types of design problems are discussed, namely for item pools for linear tests, item pools computerized adaptive testing (CAT), and systems of rotating item pools for CAT. The paper concludes with an empirical example of the problem of designing a system of rotating item pools for CAT.},
	keywords = {Adaptive Testing, Computer Assisted, Computer Programming, Educational Measurement, Item Response Theory, Mathematics, Psychometrics, Statistical Rotation computerized adaptive testing, Test Items, Testing},
	isbn = {02-09},
	author = {Veldkamp, B. P. and van der Linden, W. J. and Ariel, A.}
}
@booklet {1533,
	title = {Modifications of the Sympson-Hetter method for item-exposure control in computerized adaptive testing},
	year = {2002},
	address = {Manuscript submitted for publication},
	author = {van der Linden, W. J.}
}
@article {417,
	title = {Multidimensional adaptive testing with constraints on test content},
	journal = {Psychometrika},
	volume = {67},
	number = {4},
	year = {2002},
	note = {Psychometric Society, US},
	pages = {575-588},
	abstract = {The case of adaptive testing under a multidimensional response model with large numbers of constraints on the content of the test is addressed. The items in the test are selected using a shadow test approach. The 0{\textendash}1 linear programming model that assembles the shadow tests maximizes posterior expected Kullback-Leibler information in the test. The procedure is illustrated for five different cases of multidimensionality. These cases differ in (a) the numbers of ability dimensions that are intentional or should be considered as ldquonuisance dimensionsrdquo and (b) whether the test should or should not display a simple structure with respect to the intentional ability dimensions.},
	author = {Veldkamp, B. P. and van der Linden, W. J.}
}
@article {396,
	title = {Computerized adaptive testing with equated number-correct scoring},
	journal = {Applied Psychological Measurement},
	volume = {25},
	number = {4},
	year = {2001},
	note = {Sage Publications, US},
	pages = {343-355},
	abstract = {A constrained computerized adaptive testing (CAT) algorithm is presented that can be used to equate CAT number-correct (NC) scores to a reference test. As a result, the CAT NC scores also are equated across administrations. The constraints are derived from van der Linden \& Luecht{\textquoteright}s (1998) set of conditions on item response functions that guarantees identical observed NC score distributions on two test forms. An item bank from the Law School Admission Test was used to compare the results of the algorithm with those for equipercentile observed-score equating, as well as the prediction of NC scores on a reference test using its test response function. The effects of the constraints on the statistical properties of the θ estimator in CAT were examined. },
	author = {van der Linden, W. J.}
}
@booklet {1345,
	title = {Implementing content constraints in a-stratified adaptive testing using a shadow test approach (Research Report 01-001)},
	year = {2001},
	address = {University of Twente, Department of Educational Measurement and Data Analysis},
	author = {Chang, Hua-Hua and van der Linden, W. J.}
}
@conference {929,
	title = {Modeling variability in item parameters in CAT},
	booktitle = {Paper presented at the Annual Meeting of the National Council on Measurement in Education},
	year = {2001},
	address = {Seattle WA},
	author = {Glas, C. A. W. and van der Linden, W. J.}
}
@conference {1212,
	title = {Using response times to detect aberrant behavior in computerized adaptive testing},
	booktitle = {Paper presented at the annual meeting of the National Council on Measurement in Education},
	year = {2001},
	address = {Seattle WA},
	author = {van der Linden, W. J. and van Krimpen-Stoop, E. M. L. A.}
}
@article {402,
	title = {Capitalization on item calibration error in adaptive testing},
	journal = {Applied Measurement in Education},
	volume = {13},
	number = {1},
	year = {2000},
	note = {References .Lawrence Erlbaum, US},
	pages = {35-53},
	abstract = {(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.},
	keywords = {computerized adaptive testing},
	author = {van der Linden, W. J. and Glas, C. A. W.}
}
@book {403,
	title = {Computerized adaptive testing: Theory and practice},
	year = {2000},
	publisher = {Kluwer Academic Publishers},
	organization = {Kluwer Academic Publishers},
	address = {Dordrecht, The Netherlands},
	author = {van der Linden, W. J. and Glas, C. A. W.}
}
@inbook {1922,
	title = {Constrained adaptive testing with shadow tests},
	year = {2000},
	address = {W. J. van der Linden and C. A. W. Glas (eds.), Computerized adaptive testing: Theory and practice (pp.27-52). Norwell MA: Kluwer.},
	author = {van der Linden, W. J.}
}
@inbook {1925,
	title = {Cross-validating item parameter estimation in adaptive testing},
	year = {2000},
	address = {A. Boorsma, M. A. J. van Duijn, and T. A. B. Snijders (Eds.) (pp. 205-219), Essays on item response theory. New York: Springer.},
	author = {van der Linden, W. J. and Glas, C. A. W.}
}
@inbook {416,
	title = {Designing item pools for computerized adaptive testing},
	booktitle = {Computerized adaptive testing: Theory and practice},
	year = {2000},
	pages = {149{\textendash}162},
	publisher = {Kluwer Academic Publishers},
	organization = {Kluwer Academic Publishers},
	address = {Dendrecht, The Netherlands},
	author = {Veldkamp, B. P. and van der Linden, W. J.}
}
@article {409,
	title = {An integer programming approach to item bank design},
	journal = {Applied Psychological Measurement},
	volume = {24},
	number = {2},
	year = {2000},
	pages = {139-150},
	abstract = {An integer programming approach to item bank design is presented that can be used to calculate an optimal blueprint for an item bank, in order to support an existing testing program. The results are optimal in that they minimize the effort involved in producing the items as revealed by current item writing patterns. Also presented is an adaptation of the models, which can be used as a set of monitoring tools in item bank management. The approach is demonstrated empirically for an item bank that was designed for the Law School Admission Test. },
	keywords = {Aptitude Measures, Item Analysis (Test), Item Response Theory, Test Construction, Test Items},
	author = {van der Linden, W. J. and Veldkamp, B. P. and Reese, L. M.}
}
@inbook {404,
	title = {Item selection and ability estimation in adaptive testing},
	booktitle = {Computerized adaptive testing: Theory and practice},
	year = {2000},
	pages = {1{\textendash}25},
	publisher = {Kluwer Academic Publishers},
	organization = {Kluwer Academic Publishers},
	address = {Dordrecht, The Netherlands},
	author = {van der Linden, W. J. and Pashley, P. J.}
}
@booklet {1549,
	title = {Multidimensional adaptive testing with constraints on test content (Research Report 00-11)},
	year = {2000},
	address = {Enschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis},
	author = {Veldkamp, B. P. and van der Linden, W. J.}
}
@booklet {1532,
	title = {Optimal stratification of item pools in a-stratified computerized adaptive testing (Research Report 00-07)},
	year = {2000},
	address = {Enschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis},
	author = {van der Linden, W. J.}
}
@booklet {1538,
	title = {Using response times to detect aberrant behavior in computerized adaptive testing (Research Report 00-09)},
	year = {2000},
	address = {Enschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis},
	author = {van der Linden, W. J. and van Krimpen-Stoop, E. M. L. A.}
}
@booklet {1531,
	title = {Adaptive testing with equated number-correct scoring (Research Report 99-02)},
	year = {1999},
	address = {Enschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis},
	author = {van der Linden, W. J.}
}
@booklet {1548,
	title = {Designing item pools for computerized adaptive testing (Research Report 99-03 )},
	year = {1999},
	address = {Enschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis},
	author = {Veldkamp, B. P. and van der Linden, W. J.}
}
@article {740,
	title = {Empirical initialization of the trait estimator in adaptive testing},
	journal = {Applied Psychological Measurement},
	volume = {23},
	year = {1999},
	note = {[Error correction in 23, 248]},
	pages = {21-29},
	author = {van der Linden, W. J.}
}
@inbook {1921,
	title = {Het ontwerpen van adaptieve examens [Designing adaptive tests]},
	year = {1999},
	note = {[In Dutch]},
	address = {J. M Pieters, Tj. Plomp, and L.E. Odenthal (Eds.), Twintig jaar Toegepaste Onderwijskunde: Een kaleidoscopisch overzicht van Twents onderwijskundig onderzoek (pp. 249-267). Enschede: Twente University Press.},
	author = {van der Linden, W. J.}
}
@article {395,
	title = {Multidimensional adaptive testing with a minimum error-variance criterion},
	journal = {Journal of Educational and Behavioral Statistics},
	volume = {24},
	number = {4},
	year = {1999},
	pages = {398-412},
	abstract = {Adaptive testing under a multidimensional logistic response model is addressed. An algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood estimator of a linear combination of abilities of interest. The criterion results in a closed-form expression that is easy to evaluate. In addition, it is shown how the algorithm can be modified if the interest is in a test with a "simple ability structure". The statistical properties of the adaptive ML estimator are demonstrated for a two-dimensional item pool with several linear combinations of the abilities. },
	keywords = {computerized adaptive testing},
	author = {van der Linden, W. J.}
}
@article {406,
	title = {Using response-time constraints to control for differential speededness in computerized adaptive testing},
	journal = {Applied Psychological Measurement},
	volume = {23},
	number = {3},
	year = {1999},
	note = {Sage Publications, US},
	pages = {195-210},
	abstract = {An item-selection algorithm is proposed for neutralizing the differential effects of time limits on computerized adaptive test scores. The method is based on a statistical model for distributions of examinees{\textquoteright} response times on items in a bank that is updated each time an item is administered. Predictions from the model are used as constraints in a 0-1 linear programming model for constrained adaptive testing that maximizes the accuracy of the trait estimator. The method is demonstrated empirically using an item bank from the Armed Services Vocational Aptitude Battery. },
	keywords = {computerized adaptive testing},
	author = {van der Linden, W. J. and Scrams, D. J. and Schnipke, D. L.}
}
@article {737,
	title = {Bayesian item selection criteria for adaptive testing},
	journal = {Psychometrika},
	volume = {63},
	year = {1998},
	pages = {201-216},
	author = {van der Linden, W. J.}
}
@booklet {1535,
	title = {Capitalization on item calibration error in adaptive testing (Research Report 98-07)},
	year = {1998},
	address = {Enschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis},
	author = {van der Linden, W. J. and Glas, C. A. W.}
}
@article {405,
	title = {A model for optimal constrained adaptive testing},
	journal = {Applied Psychological Measurement},
	volume = {22},
	number = {3},
	year = {1998},
	note = {Sage Publications, US},
	pages = {259-270},
	abstract = {A model for constrained computerized adaptive testing is proposed in which the information in the test at the trait level (0) estimate is maximized subject to a number of possible constraints on the content of the test. At each item-selection step, a full test is assembled to have maximum information at the current 0 estimate, fixing the items already administered. Then the item with maximum in-formation is selected. All test assembly is optimal because a linear programming (LP) model is used that automatically updates to allow for the attributes of the items already administered and the new value of the 0 estimator. The LP model also guarantees that each adaptive test always meets the entire set of constraints. A simulation study using a bank of 753 items from the Law School Admission Test showed that the 0 estimator for adaptive tests of realistic lengths did not suffer any loss of efficiency from the presence of 433 constraints on the item selection process. },
	keywords = {computerized adaptive testing},
	author = {van der Linden, W. J. and Reese, L. M.}
}
@article {738,
	title = {Optimal test assembly of psychological and educational tests},
	journal = {Applied Psychological Measurement},
	volume = {22},
	year = {1998},
	pages = {195-211},
	author = {van der Linden, W. J.}
}
@article {739,
	title = {Stochastic order in dichotomous item response models for fixed, adaptive, and multidimensional tests},
	journal = {Psychometrika},
	volume = {63},
	year = {1998},
	pages = {211-226},
	author = {van der Linden, W. J.}
}
@booklet {1537,
	title = {Using response-time constraints to control for differential speededness in adaptive testing (Research Report 98-06)},
	year = {1998},
	address = {Enschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis},
	author = {van der Linden, W. J. and Scrams, D. J. and Schnipke, D. L.}
}
@conference {1210,
	title = {Detection of aberrant response patterns in CAT},
	booktitle = {Paper presented at the annual meeting of the National Council on Measurement in Education},
	year = {1997},
	address = {Chicago IL},
	author = {van der Linden, W. J.}
}
@booklet {1530,
	title = {Multidimensional adaptive testing with a minimum error-variance criterion (Research Report 97-03)},
	year = {1997},
	address = {Enschede, The Netherlands: University of Twente, Department of Educational Measurement and Data Analysis},
	author = {van der Linden, W. J.}
}
@conference {1209,
	title = {Multidimensional adaptive testing with a minimum error-variance criterion},
	booktitle = {Paper presented at the annual meeting of the American Educational Research Association},
	year = {1997},
	address = {Chicago},
	author = {van der Linden, W. J.}
}
@article {736,
	title = {Bayesian item selection criteria for adaptive testing},
	journal = {Psychometrika},
	volume = {63},
	year = {1996},
	pages = {201-216},
	author = {van der Linden, W. J.}
}
@booklet {1529,
	title = {Bayesian item selection criteria for adaptive testing (Research Report 96-01)},
	year = {1996},
	address = {Twente, The Netherlands: Department of Educational Measurement and Data Analysis},
	author = {van der Linden, W. J.}
}
@conference {1208,
	title = {Bayesian item selection in adaptive testing},
	booktitle = {Paper presented at the Annual Meeting of the Psychometric Society},
	year = {1995},
	address = {Minneapolis MN},
	author = {van der Linden, W. J.}
}
@article {749,
	title = {Some procedures for computerized ability testing},
	journal = {International Journal of Educational Research},
	volume = {13(2)},
	year = {1989},
	pages = {175-187},
	author = {van der Linden, W. J. and Zwarts, M. A.}
}
