Detecting DIF in the Multi-Unidimensional Pairwise Preference (MUPP) IRT Model

• In Event: Differential Item Functioning II

Abstract

Multidimensional forced-choice (MFC) measures are gaining prominence in noncognitive assessment. Yet there has been little research on detecting differential item functioning (DIF) with models for forced-choice measures. This research examines Lord’s chi-square and item parameter replication (IPR) methods with MFC tests based on the Multi-Unidimensional Pairwise Preference (MUPP) model.

Authors

• Lavanya Shravan Kumar, UNIVERSITY OF SOUTH FLORIDA

• Naidan Tu, University of South Florida

• Sean Joo, University of Kansas

• Stephen Stark, UNIVERSITY OF SOUTH FLORIDA