Detecting Multidimensional Differential Item Functioning with the Multiple Indicators Multiple Causes Model, the Item Response Theory Likelihood Ratio Test, and Logistic Regression - Bulut, Okan; Suh, Youngsuk (Frontiers in Education, 2017)
Differential item functioning (DIF) is typically evaluated in educational assessments with a simple structure in which items are associated with a single latent trait. This study aims to extend the investigation of DIF for multidimensional assessments with a nonsimple structure in which items can be associated with two or more latent traits. A simulation study was conducted with the multidimensional extensions of the item response theory likelihood ratio (IRT-LR) test, the multiple indicators multiple causes (MIMIC) model, and logistic regression for detecting uniform and nonuniform DIF in multidimensional assessments. The results indicated that the IRT-LR test outperformed the MIMIC and logistic regression approaches in detecting nonuniform DIF. When detecting uniform DIF, the MIMIC and logistic regression approaches appeared to perform better than the IRT-LR test in short tests, while the performances of all three approaches were very similar in longer tests. Type I error rates for logistic regression were severely inflated compared to the other two approaches. The IRT-LR test appears to be a more balanced and powerful method than the MIMIC and logistic regression approaches in detecting DIF in multidimensional assessments with a nonsimple structure.