Using Credible Intervals to Detect Differential Item Functioning in IRT Models

Differential item functioning (DIF) occurs when individuals from different groups with the same level of ability have different probabilities of answering an item correctly. In this paper, we develop a Bayesian approach to detect DIF based on the credible intervals within the framework of item response theory models. Our method performed well for both uniform and non-uniform DIF conditions in the two-parameter logistic model. The efficacy of the proposed approach is demonstrated through simulation studies and a real data application.

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