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Andrich, David; Humphry, Stephen M.; Marais, Ida – Applied Psychological Measurement, 2012
Models of modern test theory imply statistical independence among responses, generally referred to as "local independence." One violation of local independence occurs when the response to one item governs the response to a subsequent item. Expanding on a formulation of this kind of violation as a process in the dichotomous Rasch model,…
Descriptors: Test Theory, Models, Item Response Theory, Evidence
van der Linden, Wim J. – Applied Psychological Measurement, 2009
An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…
Descriptors: Simulation, Adaptive Testing, Vocational Aptitude, Bayesian Statistics

Sanders, Piet F.; Verschoor, Alfred J. – Applied Psychological Measurement, 1998
Presents minimization and maximization models for parallel test construction under constraints. The minimization model constructs weakly and strongly parallel tests of minimum length, while the maximization model constructs weakly and strongly parallel tests with maximum test reliability. (Author/SLD)
Descriptors: Algorithms, Models, Reliability, Test Construction

Embretson, Susan E. – Applied Psychological Measurement, 1996
Conditions under which interaction effects estimated from classical total scores, rather than item response theory trait scores, can be misleading are discussed with reference to analysis of variance (ANOVA). When no interaction effects exist on the true latent variable, spurious interaction effects can be observed from the total score scale. (SLD)
Descriptors: Analysis of Variance, Interaction, Item Response Theory, Models
van der Linden, Wim J. – Applied Psychological Measurement, 2006
Traditionally, error in equating observed scores on two versions of a test is defined as the difference between the transformations that equate the quantiles of their distributions in the sample and population of test takers. But it is argued that if the goal of equating is to adjust the scores of test takers on one version of the test to make…
Descriptors: Equated Scores, Evaluation Criteria, Models, Error of Measurement