Research has shown that multiple-indicator multiple-cause (MIMIC) models can result in inflated Type I error rates in detecting differential item functioning (DIF) when the assumption of equal latent variance is violated. This study explains how the violation of the equal variance assumption adversely impacts the detection of nonuniform DIF and…

This study presents a generalized version of the residual differential item functioning (RDIF) detection framework in item response theory, named GRDIF, to analyze differential item functioning (DIF) in multiple groups. The GRDIF framework retains the advantages of the original RDIF framework, such as computational efficiency and ease of…

Several marginal effect size (ES) statistics suitable for quantifying the magnitude of differential item functioning (DIF) have been proposed in the area of item response theory; for instance, the Differential Functioning of Items and Tests (DFIT) statistics, signed and unsigned item difference in the sample statistics (SIDS, UIDS, NSIDS, and…

The purpose of this study is to develop a nonparametric DIF method that (a) compares focal groups directly to the composite group that will be used to develop the reported test score scale, and (b) allows practitioners to explore for DIF related to focal groups stemming from multicategorical variables that constitute a small proportion of the…

We revisit the empirically observed positive correlation between DIF and difficulty studied by Freedle and commonly seen in tests of verbal proficiency when comparing populations of different mean latent proficiency levels. It is shown that a positive correlation between DIF and difficulty estimates is actually an expected result (absent any true…

Differential bundle functioning (DBF) has been proposed to quantify the accumulated amount of differential item functioning (DIF) in an item cluster/bundle (Douglas, Roussos, and Stout). The simultaneous item bias test (SIBTEST, Shealy and Stout) has been used to test for DBF (e.g., Walker, Zhang, and Surber). Research on DBF may have the…

This study addresses the topic of how anchoring methods for differential item functioning (DIF) analysis can be used in multigroup scenarios. The direct approach would be to combine anchoring methods developed for two-group scenarios with multigroup DIF-detection methods. Alternatively, multiple tests could be carried out. The results of these…

For assessment scales applied to different groups (e.g., students from different states; patients in different countries), multigroup differential item functioning (MG-DIF) needs to be evaluated in order to ensure that respondents with the same trait level but from different groups have equal response probabilities on a particular item. The…

The field of educational measurement places validity and fairness as central concepts of assessment quality. Prior research has proposed embedding fairness arguments within argument-based validity processes, particularly when fairness is conceived as comparability in assessment properties across groups. However, we argue that a more flexible…

In the logistic regression (LR) procedure for differential item functioning (DIF), the parameters of LR have often been estimated using maximum likelihood (ML) estimation. However, ML estimation suffers from the finite-sample bias. Furthermore, ML estimation for LR can be substantially biased in the presence of rare event data. The bias of ML…

This article explores the amount of equating error at a passing score when equating scores from exams with small samples sizes. This article focuses on equating using classical test theory methods of Tucker linear, Levine linear, frequency estimation, and chained equipercentile equating. Both simulation and real data studies were used in the…

When contextual features of test-taking environments differentially affect item responding for different test takers and these features vary across test administrations, they may cause differential item functioning (DIF) that varies across test administrations. Because many common DIF detection methods ignore potential DIF variance, this article…

In typical differential item functioning (DIF) assessments, an item's DIF status is not influenced by its status in previous test administrations. An item that has shown DIF at multiple administrations may be treated the same way as an item that has shown DIF in only the most recent administration. Therefore, much useful information about the…

Test items must often be broad in scope to be ecologically valid. It is therefore almost inevitable that secondary dimensions are introduced into a test during test development. A cognitive test may require one or more abilities besides the primary ability to correctly respond to an item, in which case a unidimensional test score overestimates the…

Numerous researchers have proposed methods for evaluating the quality of rater-mediated assessments using nonparametric methods (e.g., kappa coefficients) and parametric methods (e.g., the many-facet Rasch model). Generally speaking, popular nonparametric methods for evaluating rating quality are not based on a particular measurement theory. On…