Multidimensional computerized adaptive testing (MCAT) is able to provide a vector of ability estimates for each examinee, which could be used to provide a more informative profile of an examinee's performance. The current literature on MCAT focuses on the fixed-length tests, which can generate less accurate results for those examinees whose…

In this study, the estimation of extremely large or extremely small proficiency levels, given the item parameters of a logistic item response model, is investigated. On one hand, the estimation of proficiency levels by maximum likelihood (ML), despite being asymptotically unbiased, may yield infinite estimates. On the other hand, with an…

Differential item functioning (DIF) of items has become an important issue in test fairness and equity in large-scale assessments. DIF occurs when subgroups of test takers have equal trait levels but differ in their probabilities of a correct response. DIF items may threaten the validity of test scores for subgroups and can mislead researchers…

For one reason or another, various sources of information, namely, ancillary variables and correlational structure of the latent abilities, which are usually available in most testing situations, are ignored in ability estimation. A general model that incorporates these sources of information is proposed in this article. The model has a general…

Assessments consisting of different domains (e.g., content areas, objectives) are typically multidimensional in nature but are commonly assumed to be unidimensional for estimation purposes. The different domains of these assessments are further treated as multi-unidimensional tests for the purpose of obtaining diagnostic information. However, when…

Recent work has shown that multidimensionally scoring responses from different tests can provide better ability estimates. For educational assessment data, applications of this approach have been limited to binary scores. Of the different variants, the de la Torre and Patz model is considered more general because implementing the scoring procedure…

The validation of cognitive attributes required for correct answers on binary test items or tasks has been addressed in previous research through the integration of cognitive psychology and psychometric models using parametric or nonparametric item response theory, latent class modeling, and Bayesian modeling. All previous models, each with their…

Investigated the effect of item parameter drift on ability estimates under item response theory, simulating item response data for two testing occasions for the two-parameter logistic model under several crossed conditions. Results show that item parameter drift under the simulated conditions had a small effect on ability estimates. (SLD)

Develops an item-parameter estimation procedure using an EM algorithm for the continuous-response model (F. Samejima, 1973). Examines the usefulness of this model using simulated data. Results show that the procedure performs well in estimating items and theta parameters. (SLD)

This study compared the Mantel-Haenszel procedure, the simultaneous item bias approach (SIB), and the logistic regression approach (LR) with respect to Type I error rates and power to detect nonuniform differential item functioning (DIF). The SIB and LR procedures were equally powerful in detecting nonuniform DIF. (SLD)

Presents two mathematical programming approaches for the assembly of ability tests from item pools calibrated under a multidimensional item response theory model. Item selection is based on the Fisher information matrix. Illustrates the method through empirical examples for a two-dimensional mathematics item pool. (SLD)

Studied the effects of test dimensionality, theta distribution shape, and estimation program (BILOG, MULTILOG, or XCALIBRE) on the accuracy of item and person parameter estimates through simulation. Derived guidelines for estimating parameters of multidimensional test items using unidimensional item response theory models. (SLD)

Item response theory equating invariance was examined by simulating vertical equating of two sets of examinee ability data comparing Rasch, three-parameter, and equipercentile equating methods. All three were reasonably invariant, suggesting that multidimensionality is likely to be the cause of lack of invariance found in real data sets. (SLD)

Presents a characteristic curve procedure for comparing transformations of the item response theory ability scale assuming the multiple-choice model. Illustrates the use of the method with an example equating American College Testing mathematics tests. (SLD)

The concept of item discrimination is generalized to the case in which more than one ability is required to determine the correct response to an item, using the conceptual framework of item response theory and the definition of multidimensional item difficulty previously developed by M. Reckase (1985). (SLD)