Evaluation of covariate effects in item response theory models

Abstract Item response theory (IRT) models are usually the best way to analyze composite or rating scale data. Standard methods to evaluate covariate or treatment effects in IRT models do not allow to identify item‐specific effects. Finding subgroups of patients who respond differently to certain items could be very important when designing inclusion or exclusion criteria for clinical trials, and aid in understanding different treatment responses in varying disease manifestations. We present a new method to investigate item‐specific effects in IRT models, which is based on inspection of residuals. The method was investigated in a simulation exercise with a model for the Epworth Sleepiness Scale. We also provide a detailed discussion as a guidance on how to build a robust covariate IRT model.