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

Author(s):
Fu, Jianbin
Publication Year:
2016
Report Number:
RR-16-21
Source:
ETS Research Report
Document Type:
Report
Page Count:
14
Subject/Key Words:
Academic Skills Covariates Differential Item Functioning (DIF) Group Differences Individual Differences Item Response Theory (IRT) Longitudinal Data Model Fit Multidimensional Item Response Theory (MIRT)

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.

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