Test data generated according to two different multidimensional item response theory (IRT) models were compared at both the item response level and the test score level to determine whether measurable differences between the models could be detected when the data sets were constrained to be equivalent in terms of item "p"-values. The…

A model of test item dependency is presented and used to illustrate the effect that violations of local independence have on the behavior of item characteristic curves. The dependency model is flexible enough to simulate the interaction of a number of factors including item difficulty and item discrimination, varying degrees of item dependence,…

The effect of large, within-examinee item difficulty variability on estimates of the proportion of consistent classification of examinees into mastery categories was studied over 2 test administrations for 100 simulated examinees. The proportion of consistent classifications was adequately estimated using the technique proposed by M. Subkoviak…

Presents logistic discriminant analysis as a means of detecting differential item functioning (DIF) in items that are polytomously scored. Provides examples of DIF detection using a 27-item mathematics test with 1,977 examinees. The proposed method is simpler and more practical than polytomous extensions of the logistic regression DIF procedure.…

The purpose of this study was to examine the effect that large within-examinee item difficulty variability had on estimates of the proportion of consistent classification of examinees into mastery categories over two test administrations. The classification consistency estimate was based on a single test administration from an estimation procedure…

A popular method of analyzing test items for differential item functioning (DIF) is to compute a statistic that conditions samples of examinees from different populations on an estimate of ability. This conditioning or matching by ability is intended to produce an appropriate statistic that is sensitive to true differences in item functioning,…

This paper discussed methods currently under study for use with multiple-response data. Besides using Bonferroni inequality methods to control type one error rate over a set of inferences involving multiple response data, a recently proposed methodology of plotting the p-values resulting from multiple significance tests was explored. Proficiency…