This paper uses a Bayesian approach for parameter estimation in Item Response Theory Models for DIF - Differential Item Functioning - analysis. The models proposed are integrated, and incorporate regression structures that can be used to explain the DIF related to items associated covariates. The models are proposed for multiple groups and the approach used, naturally, consider the estimation error of the latent trace and the estimation error of the structural parameters. Examples with simulated data and real data are also presented.
item differential functioning; MCMC; item response theory
