This dissertation aims to investigate the effect size measures of differential item functioning (DIF) detection in the context of cognitive diagnostic models (CDMs). A variety of DIF detection techniques have been developed in the context of CDMs. However, most of the DIF detection procedures focus on the null hypothesis significance test. Few…

This rejoinder keeps the original focus on statistical computing pertaining to the correlation of student achievement between mathematics and science from the Trend in Mathematics and Science Study (TIMSS). Albeit the availability of student performance data in TIMSS and the emphasis of the inter-subject connection in the Next Generation Science…

Purpose: Studies in the literature have generally demonstrated that the causes of differential item functioning (DIF) are complex and not directly related to defined groups. The purpose of this study is to determine the DIF according to the mixture item response theory (MixIRT) model, based on the latent group approach, as well as the…

Recent data have suggested that despite massive outlays on educational reform Qatar consistently ranks as one of the least academically proficient countries in key areas of literacy. Of the seventy-four countries that participated in PISA 2009 Qatar ranked between sixty-seven and sixty-nine in mathematics, reading and science literacy. Although…

Background: When studying student performance across different countries or cultures, an important aspect for comparisons is that of score comparability. In other words, it is imperative that the latent variable (i.e., construct of interest) is understood and measured equivalently across all participating groups or countries, if our inferences…

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.…