Detecting Differential Item Functioning Using SIBTEST, MH, LR and IRT Methods

In this study, differential item functioning (DIF) and differential bundle functioning (DBF) analyses of the Academic Staff and Postgraduate Education Entrance Examination Quantitative Ability Tests were carried out. Mantel-Haenszel, logistic regression, SIBTEST, Item Response Theory-Likelihood Ratio and BILOG-MG DIF Algorithm methods were used for DIF analyses. SIBTEST was the method used for DBF analyses. Data sets for the study came from an earlier application of the examination. Gender DIF analyses showed that eleven items showed DIF. Four of the items favored male applicants, where seven of them favored female applicants. In order to investigate the sources of DIF, we consulted experts. In general, the items which could be solved using routine algorithmic operations and which are presented in the algebraic, abstract format showed DIF in favor of females. The “real-life” word problems favored males. According to DBF analyses, the operations item group favored females and the word problems item group favored males