@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 {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.}
}
@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.}
}
