Bayesian inference in two-phase prevalence studies.

This paper discusses Bayesian methods for the assessment of the prevalence of a disorder based on data from a two-phase design with a short screening instrument administered at the first phase followed by an in-depth diagnostic instrument given at the second phase. In calculating the posterior distributions of the quantities of interest, for example, the prevalence, sensitivity and specificity, and predictive distributions, we used the Gibbs sampler. We illustrate our approach by assessing the prevalence of depression in adolescents with use of data attained from a two-phase design.