Presents an adaptive approach to multiple significance testing based on the procedure of Y. Benjamini and Y. Hochberg (1995) that first estimates the number of true null hypotheses and then uses that estimate in the Benjamini and Hochberg procedure. Uses the new procedure in examples from educational and behavioral studies and shows its control of…

The purpose of this study was to investigate and to quantify the tolerable error in item parameter estimates for different sets of items used in computer-based testing. The study examined items that were administered repeatedly to different examinee samples over time, examining items that were administered linearly in a fixed order each time they…

Reviewed methods of estimating theta suitable for computerized adaptive testing (CAT) and discussed the differences between Fisher and Kullback-Leibler information criteria for selecting items. Examined the accuracy of different CAT algorithms using samples from the National Assessment of Educational Progress. Results show when correcting for…

The purpose of this Monte Carlo study was to evaluate the relative accuracy of T. Warm's weighted likelihood estimate (WLE) compared to maximum likelihood estimate (MLE), expected a posteriori estimate (EAP), and maximum a posteriori estimate (MAP), using the generalized partial credit model (GPCM) and graded response model (GRM) under a variety…

Item scores that do not fit an assumed item response theory model may cause the latent trait value to be estimated inaccurately. Several person-fit statistics for detecting nonfitting score patterns for paper-and-pencil tests have been proposed. In the context of computerized adaptive tests (CAT), the use of person-fit analysis has hardly been…

Two methods for estimating the reliability of a computerized adaptive test (CAT) without using item response theory are presented. The data consist of CAT and paper-and-pencil scores from identical or equivalent samples, and scores for all examinees on one or more covariates, using the Armed Services Vocational Aptitude Battery. (TJH)

Performed a simulation study to demonstrate the dramatic impact of capitalization on estimation errors on ability estimation in adaptive testing. Discusses four different strategies to minimize the likelihood of capitalization in computerized adaptive testing. (SLD)

Test security has often been a problem in computerized adaptive testing (CAT) because the traditional wisdom of item selection overly exposes high discrimination items. The a-stratified (STR) design advocated by H. Chang and his collaborators, which uses items of less discrimination in earlier stages of testing, has been shown to be very…

In the a-stratified method, a popular and efficient item exposure control strategy proposed by H. Chang (H. Chang and Z. Ying, 1999; K. Hau and H. Chang, 2001) for computerized adaptive testing (CAT), the item pool and item selection process has usually been divided into four strata and the corresponding four stages. In a series of simulation…

Item response theory (IRT) has been adapted as the theoretical foundation of computerized adaptive testing (CAT) for several decades. In applying IRT to CAT, there are certain considerations that are essential, and yet tend to be neglected. These essential issues are addressed in this paper, and then several ways of eliminating noise and bias in…

A study was conducted to investigate whether augmenting the calibration of items using computerized adaptive test (CAT) data matrices produced estimates that were unbiased and improved the stability of existing item parameter estimates. Item parameter estimates from four pools of items constructed for operational use were used in the study to…

The reliability coefficient is predicted from the test information function (TIF) or two modified TIF formulas and a specific trait distribution. Examples illustrate the variability of the reliability coefficient across different trait distributions, and results are compared with empirical reliability coefficients. (SLD)

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…

Compared five item selection rules with respect to the efficiency and precision of trait (theta) estimation at the early stages of computerized adaptive testing (CAT). The Fisher interval information, Fisher information with a posterior distribution, Kullback-Leibler information, and Kullback-Leibler information with a posterior distribution…

In the process of item calibration for a computerized adaptive test (CAT), many well-established calibrating packages show weakness in the estimation of item parameters. This paper introduces an on-line calibration algorithm based on the convexity of likelihood functions. This package consists of: (1) an algorithm that estimates examinee ability…