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