Detection of differential item functioning in large-scale state assessments: A study evaluating a two-stage approach

In differential item functioning (DIF) studies, examinees from different groups are typically ability matched, and then one or more statistical indices are used to compare performance on a set of test items. Typically, matching is on total test score (a criterion both observable and easily accessible), but it may be limited in value because if DIF is present, it is likely to distort test scores and potentially confound any item performance differences. Thus, some researchers have advocated iterative approaches for DIF detection. In this article, a two-stage methodology for evaluating DIF in large-scale state assessment data was explored. The findings illustrated the merit of iterative approaches for DIF detection. Items being flagged as DIF in the second stage were not necessarily the same items identified as DIF in the first stage and vice versa, and this finding was directly related to the amount of DIF found in the Stage 1 analyses.