Detecting Differential Item Functioning in CAT Using IRT Residual DIF Approach

Abstract

The residual differential item functioning (RDIF) detection framework was developed recently under a linear testing context. To explore the potential application of this framework to computerized adaptive testing (CAT), the present study investigated the utility of the RDIF_R statistic both as an index for detecting uniform DIF of pretest items in CAT and as a direct measure of the effect size of uniform DIF. Extensive CAT simulations revealed RDIF_R to have well-controlled Type I error and slightly higher power to detect uniform DIF compared with CATSIB, especially when pretest items were calibrated using fixed-item parameter calibration. Moreover, RDIF_R accurately estimated the amount of uniform DIF irrespective of the presence of impact. Therefore, RDIF_R demonstrates its potential as a useful tool for evaluating both the statistical and practical significance of uniform DIF in CAT.