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

Abstract

The multidimensional item response theory ( MIRT ) models with covariates proposed by Haberman and implemented in the mirt program provide a flexible way to analyze data based on item response theory. In this report, we discuss 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 procedure to identify common items with item drift across test occasions, and model selection and evaluation based on model comparison, fit statistics, and skill estimates. A real dataset on algebra tests is used to demonstrate the applications. Report Number: ETS RR‐16–21