Detection of Crossing Differential Item Functioning

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Abstract
Differential item functioning (DIF) continues to receive attention both in applied and methodological studies. Because DIF can be an indicator of irrelevant variance that can influence test scores, continuing to evaluate and improve the accuracy of detection methods is an essential step in gathering score validity evidence. Methods for detecting uniform DIF are well established, whereas those for identifying the presence of nonuniform or crossing DIF are less clearly understood. Four such methods were compared: simultaneous item bias test (SIBTEST), logistic regression, item response theory likelihood ratio test, and confirmatory factor analysis. Factors manipulated were sample size, ability differences between groups, percentage of DIF, and the underlying model used to generate the data. Results suggest that all methods were able to control Type I error, but SIBTEST had the highest power of the approaches compared. Problems with detection rates were evident with different underlying models.

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