Application of Bayesian item selection criteria in computerized adaptive testing might result in improvement of bias and MSE of the ability estimates. The question remains how to apply Bayesian item selection criteria in the context of constrained adaptive testing, where large numbers of specifications have to be taken into account in the item…

In measurement research, data simulations are a commonly used analytical technique. While simulation designs have many benefits, it is unclear if these artificially generated datasets are able to accurately capture real examinee item response behaviors. This potential lack of comparability may have important implications for administration of…

Proposes a model for constrained computerized adaptive testing in which the information in the test at the trait level (theta) estimate is maximized subject to the number of possible constraints on the content of the test. Test assembly relies on a linear-programming approach. Illustrates the approach through simulation with items from the Law…

This study investigated the applicability to computerized adaptive testing (CAT) data of a differential item functioning (DIF) analysis that involves an empirical Bayes (EB) enhancement of the popular Mantel Haenszel (MH) DIF analysis method. The computerized Law School Admission Test (LSAT) assumed for this study was similar to that currently…

Developed a multilevel item response (IRT) model that allows for differences between the distributions of item parameters of families of item clones. Results from simulation studies based on an item pool from the Law School Admission Test illustrate the accuracy of the item pool calibration and adaptive testing procedures based on the model. (SLD)

A model for constrained computerized adaptive testing is proposed in which the information on 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…

The use of indices and statistics based on nonlinear factor analysis (NLFA) has become increasingly popular as a means of assessing the dimensionality of an item response matrix. Although the indices and statistics currently available to the practitioner have been shown to be useful and accurate in many testing situations, few studies have…

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…

A considerable amount of data on computerized adaptive testing (CAT) has been conducted using simulated data. However, most researchers would agree that simulations may not fully reflect the reality of examinee performance on a test. This study used maximum likelihood procedures to investigate the accuracy and efficiency of examinee ability…