This article illustrates the use of an explanatory item response modeling (EIRM) approach in the context of measuring group differences in science achievement. The distinction between item response models and EIRMs, recently elaborated by De Boeck and Wilson (2004), is presented within the statistical framework of generalized linear mixed models.…

Three methods of detecting item drift were compared: the procedure in BILOG-MG for estimating linear trends in item difficulty, the CUSUM procedure that Veerkamp and Glas (2000) used to detect trends in difficulty or discrimination, and a modification of Kim, Cohen, and Park's (1995) x 2 test for multiple-group differential item functioning (DIF),…

The accurate measurement of examinee test performance is critical to educational decision-making, and inaccurate measurement can lead to negative consequences for examinees. Person-fit statistics are important in a psychometric analysis for detecting examinees with aberrant response patterns that lead to inaccurate measurement. Unfortunately,…

Recently, nonparametric methods have been proposed that provide a dimensionally based description of test structure for tests with dichotomous items. Because such methods are based on different notions of dimensionality than are assumed when using a psychometric model, it remains unclear whether these procedures might lead to a different…

This research examined the degree of comparability and sources of incomparability of English and French versions of reading, mathematics, and science tests that were administered as part of a survey of achievement in Canada. The results point to substantial psychometric differences between the 2 language versions. Approximately 18% to 36% of the…