MIMIC Methods for Detecting DIF Among Multiple Groups: Exploring a New Sequential-Free Baseline Procedure

A simulation study was conducted to investigate the efficacy of multiple indicators multiple causes (MIMIC) methods for multi-group uniform and non-uniform differential item functioning (DIF) detection. DIF was simulated to originate from one or more sources involving combinations of two background variables, gender and ethnicity. Three implementations of MIMIC DIF methods were compared: constrained baseline, free baseline, and a new sequential-free baseline. When the MIMIC assumption of equal factor variance across comparison groups was satisfied, the sequential-free baseline method provided excellent Type I error and power, with results similar to an idealized free baseline method that used a designated DIF-free anchor, and results much better than a constrained baseline method, which used all items other than the studied item as an anchor. However, when the equal factor variance assumption was violated, all methods showed inflated Type I error. Finally, despite the efficacy of the two free baseline methods for detecting DIF, identifying the source(s) of DIF was problematic, especially when background variables interacted.