Two IRT Fixed Parameter Calibration Methods for the Bifactor Model

Abstract

New items are often evaluated prior to their operational use to obtain item response theory (IRT) item parameter estimates for quality control purposes. Fixed parameter calibration is one linking method that is widely used to estimate parameters for new items and place them on the desired scale. This article provides detailed descriptions of two fixed parameter calibration methods for the bifactor model and compares their relative performance through simulation. The two methods, which were natural generalizations of their counterparts in the unidimensional context, are the one prior weights updating and multiple expectation-maximization (EM) cycles (OWU-MEM) and multiple prior weights updating and multiple EM cycles (MWU-MEM) methods. In addition, for comparison purposes, the separate calibration method with Haebara linking was included in the simulation. In general, the MWU-MEM method recovered item parameters well for both equivalent and nonequivalent groups, whereas the OWU-MEM method worked well only for equivalent groups. With a few exceptions, the MWU-MEM and Haebara methods showed comparable item parameter recovery.