A Multilevel Item Response Theory Modeling Framework for Detecting Differential Item Functioning

• In Event: Poster Session 6
  In Poster Session: Advanced Issues in Multilevel Modeling

Abstract

Multilevel item response theory (IRT) models have been suggested as a useful methodology for detecting differential item functioning (DIF) of a test or a rating scale. The purpose of this study is to construct a hierarchical generalized linear model (HGLM) based on the IRT framework to analyze a teacher evaluation instrument with ordinal categories and then to detect DIF by considering respondents’ personal attributes. Results of this study indicated that personal attributes failed to biase their ratings of teaching quality and this instrument successfully indicated specific issues of teaching behavior. This study suggests useful modeling extensions of IRT brought by HGLM including level indicators and personal attributes as covariates that would impact item responses for the purpose of detecting DIF.

Author

• Xiaodan Tang, University of Illinois at Chicago