@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.}
}
@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 {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.}
}
@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.}
}
@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.}
}
@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 {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.}
}
@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.}
}
@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.}
}
