Abstract

AbstractThe use and interpretation of educational and psychological test scores are paramount to individual outcomes and opportunities. Methods for detecting differential item functioning (DIF) are imperative for item analysis when developing and revising assessments, particularly as it pertains to fairness across populations, languages, and cultures. We discuss the practical application of third generation of DIF, which proposes an ecological framework for explaining why DIF occurs using sociological, community, and contextual variables as possible explanations of item responding. We examined school district clusters for DIF through a model‐based approach via multilevel logistic regression random‐intercept and random‐coefficient models to detect racial/ethnic DIF on a youth risk and needs assessment. We demonstrate how the use of district‐level administrative data as estimates of student's contextual environments shows promise to understand ecological sources of DIF and DIF variance. The implication of the work progresses DIF research, enhances the approach to understanding item responses, and provides a more accurate understanding of youth development through an ecological framework. Recommendations for practice and future studies are discussed.

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