Monte Carlo simulation was used to investigate score bias and information characteristics of Owen's Bayesian adaptive testing strategy, and to examine possible causes of score bias. Factors investigated in three related studies included effects of item discrimination, effects of fixed vs. variable test length, and effects of an accurate prior…

This study explores the test-retest consistency of computer adaptive tests of varying lengths. The testing model used was designed as a mastery model to determine whether an examinee's estimated ability level is above or below a pre-established criterion expressed in the metric (logits) of the calibrated item pool scale. The Rasch model was used…

The advantages that computer adaptive testing offers over linear tests have been well documented. The Computer Adaptive Test (CAT) design is more efficient than the Linear test design as fewer items are needed to estimate an examinee's proficiency to a desired level of precision. In the ideal situation, a CAT will result in examinees answering…