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| van der Linden, Wim J. | 13 |
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| Vos, Hans J. | 2 |
| Chang, Hua-Hua | 1 |
| Mellenbergh, Gideon J. | 1 |
| Reese, Lynda M. | 1 |
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Peer reviewedvan der Linden, Wim J.; Vos, Hans J. – Psychometrika, 1996
A Bayesian approach for simultaneous optimization of test-based decisions is presented using the example of a selection decision for a treatment followed by a mastery decision. A distinction is made between weak and strong rules, and conditions for monotonicity of optimal weak and strong rules are presented. (Author/SLD)
Descriptors: Bayesian Statistics, Decision Making, Scores, Selection
Download full textvan der Linden, Wim J. – 1998
Six methods for assembling tests from a pool with an item-set structure are presented. All methods are computational and based on the technique of mixed integer programming. The methods are evaluated using such criteria as the feasibility of their linear programming problems and their expected solution times. The methods are illustrated for two…
Descriptors: Higher Education, Item Banks, Selection, Test Construction
van der Linden, Wim J.; Chang, Hua-Hua – 2001
The methods of alpha-stratified adaptive testing and constrained adaptive testing with shadow tests are combined in this study. The advantages are twofold. First, application of the shadow test allows the researcher to implement any type of constraint on item selection in alpha-stratified adaptive testing. Second, the result yields a simple set of…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Selection
Peer reviewedMellenbergh, Gideon J.; van der Linden, Wim J. – Psychometrika, 1981
A linear utility model is introduced for optimal selection where several subpopulations of applicants are to be distinguished. Using this model, procedures are described for obtaining optimal cutting scores in subpopulations in quota-free as well as quota-restricted selection situations. The procedures are demonstrated with empirical data.…
Descriptors: Culture Fair Tests, Cutting Scores, Mathematical Models, Selection
van der Linden, Wim J.; Vos, Hans J. – 1994
This paper presents some Bayesian theories of simultaneous optimization of decision rules for test-based decisions. Simultaneous decision making arises when an institution has to make a series of selection, placement, or mastery decisions with respect to subjects from a population. An obvious example is the use of individualized instruction in…
Descriptors: Bayesian Statistics, Decision Making, Foreign Countries, Scores
van der Linden, Wim J. – 1997
The case of adaptive testing under a multidimensional logistic response model is addressed. An adaptive algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The item selection criterion is a simple expression in closed form. In addition, it is…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
van der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L. – 2003
This paper proposes an item selection algorithm that can be used to neutralize the effect of time limits in computer adaptive testing. The method is based on a statistical model for the response-time distributions of the test takers on the items in the pool that is updated each time a new item has been administered. Predictions from the model are…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Linear Programming
Peer reviewedvan der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L. – Applied Psychological Measurement, 1999
Proposes an item-selection algorithm for neutralizing the differential effects of time limits on computerized adaptive test scores. Uses a statistical model for distributions of examinees' response times on items in a bank that is updated each time an item is administered. Demonstrates the method using an item bank from the Armed Services…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Banks
Peer reviewedvan der Linden, Wim J. – Psychometrika, 1981
Decision rules for assigning students to treatments based upon aptitudes or criterion scores are discussed. Popular procedures are criticized and a Bayesian approach is recommended. The effect of unreliability of aptitude or criterion scores is also discussed. (JKS)
Descriptors: Aptitude Treatment Interaction, Criterion Referenced Tests, Cutting Scores, Decision Making
van der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L. – 1998
An item-selection algorithm to neutralize the differential effects of time limits on scores on computerized adaptive tests is proposed. The method is based on a statistical model for the response-time distributions of the examinees on items in the pool that is updated each time a new item has been administered. Predictions from the model are used…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Foreign Countries
van der Linden, Wim J. – 1996
R. J. Owen (1975) proposed an approximate empirical Bayes procedure for item selection in adaptive testing. The procedure replaces the true posterior by a normal approximation with closed-form expressions for its first two moments. This approximation was necessary to minimize the computational complexity involved in a fully Bayesian approach, but…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computation
van der Linden, Wim J.; Reese, Lynda M. – 1997
A model for constrained computerized adaptive testing is proposed in which the information in the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum information at the current ability estimate fixing…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Computer Simulation
van der Linden, Wim J. – 1987
The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Four basic decision problems are distinguished: (1) selection; (2) mastery; (3) placement; and (4) classification, the situation where each treatment has its own criterion. Each type of decision can be identified as a specific configuration of one or…
Descriptors: Bayesian Statistics, Classification, Decision Making, Foreign Countries
