Simulation study of item bias detection with restricted factor analysis

Restricted factor analysis (RFA) can be used to detect item bias (also called differential item functioning). In the RFA method of item bias detection, the common factor model serves as an item response model, but group membership is also included in the model. Two simulation studies are reported, both showing that the RFA method detects bias in 7‐point scale items very well, especially when the sample size is large, the mean trait difference between groups is small, the group sizes are equal, and the amount of bias is large. The first study further shows that the RFA method detects bias in dichotomous items at least as well as an established method based on the one‐parameter logistic item response model. The second study concerns various procedures to evaluate the significance of two‐item bias indices provided by the RFA method. The results indicate that the RFA method performs best when it is used in an iterative procedure.