Logistic Regression and Its Use in Detecting Differential Item Functioning in Polytomous Items

Abstract

A computer simulation study was conducted to determine the feasibility of using logistic regression procedures to detect differential item functioning (DIF) in polytomous items. One item in a simulated test of 25 items contained DIF; parameters' for that item were varied to create three conditions of nonuniform DIF and one of uniform DIF. Item scores were generated using a generalized partial credit model, and the data were recoded into multiple dichotomies in order to use logistic regression procedures. Results indicate that logistic regression is powerful in detecting most forms of DIF; however, it required large amounts of data manipulation, and interpretation of the results was sometimes difficult. Some logistic regression procedures may be useful in the post hoc analysis of DlF for polytomous items.