Applications of Multidimensional Item Response Theory Models With Covariates to Longitudinal Test Data

• In Event: 29.082 - Roundtable Session 9
  In Roundtable Session: 29.082-14 - Linking, Equating, and Multidimensional Item Response Theory

Abstract

The multidimensional item response theory (MIRT) models with covariates proposed by Haberman (2013) and implemented in the MIRT program provide a more flexible way to analyze data based on the item response theory. In this paper, we discuss the applications of the MIRT models with covariates to longitudinal test data to measure skill differences at the individual and group levels. In particular, we describe the differential item functioning (DIF) procedure to identify common items with item drift across test occasions, and model selection and evaluation based on model comparison and fit statistics and skill estimates. A real mathematics dataset is used to demonstrate the applications.

Author

• Jianbin Fu, ETS