An extension of a bayesian approach to detect differential item functioning

The application of the existing test statistics to determine differential item functioning (DIF) requires large samples, but test administrators often face the challenge of detecting DIF with small samples. One advantage of a Bayesian approach over a frequentist approach is that the former can incorporate, in the form of a prior distribution, existing information on the inference problem at hand. Sinharay, Dorans, Grant, and Blew (2009) suggested the use of information from past data sets as a prior distribution in a Bayesian DIF analysis. This paper suggests an extension of the method of Sinharay et al. (2009). The suggested extension is compared to the existing DIF detection methods in a realistic simulation study.