SAS PROC IRT and the R Mirt Package: A Comparison of Model Parameter Estimation for Multidimensional IRT Models

Abstract

This study investigates the performance of estimation methods for multidimensional IRT models with dichotomous and polytomous data in two well-known IRT programs: SAS PROC IRT and the mirt package in R. A simulation study was used to compare performance on a simple structure Rasch model, complex structure 2PL model, and bifactor graded response model. Under RMSE and bias criteria regarding item parameter recovery, PROC IRT and mirt showed nearly identical performance in the simple structure condition. When a complex structure was used, mirt performed better in terms of the recovery of intercept parameters, while the recovery of slope parameters depended on the program and the sample sizes: PROC IRT tended to be better with small samples (N=500) according to RMSE, and mirt was better for larger samples (N=1000 and 2500) according to RMSE and bias for the slope parameter recovery. When a bifactor structure was used, mirt was preferred in all cases; differences lessened as sample size increased.