Detecting Multidimensional Differential Item Functioning with the Multiple Indicators Multiple Causes Model, the Item Response Theory Likelihood Ratio Test, and Logistic Regression

• Main Authors: Okan Bulut, Youngsuk Suh
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2017-10-01
• Series: Frontiers in Education
• Subjects: differential item functioning; multidimensional item response theory models; structural equation modeling; logistic regression; test fairness
• Online Access: http://journal.frontiersin.org/article/10.3389/feduc.2017.00051/full

Differential item functioning (DIF) is typically evaluated in educational and psychological 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 non-simple 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 non-uniform DIF in multidimensional assessments. The results indicated that the IRT-LR test outperformed the MIMIC and logistic regression approaches in detecting non-uniform 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 with 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 non-simple structure.