American Statistical Association New York City Metropolitan Area Chapter Mailman School of Public Health Columbia University Department of Biostatistics Colloquium

Mental health survey instruments are often useful at diagnosing and summarizing well-being of respondents. A typical survey involves respondents evaluating themselves on a number of items via a set of ordinal choices. If certain subgroups of patients with the same mental health status give systematically different responses to certain items, the instrument is said to exhibit differential item functioning (DIF). In this talk, we develop a Bayesian approach to identifying differences in item response patterns with particular application to Samejima's (1969) graded response model. Our approach involves positing four lack-of-fit diagnostics to examine departures from conditional independence. We apply our approach to the analysis of responses by mental health patients from the BASIS-24, a widely-used self-report mental health assessment instrument, to study differences among different cultural and language groups in item response patterns.