In this module, we discuss Bayesian hierarchical modeling and general computational methods for Bayesian estimation of hierarchical models. We apply hierarchical models to some biomedical problems including diagnostic testing in the absence of a gold standard, meta-analyses, and mixed treatment comparisons, among others.
We use INLA, JAGS and a number of R packages to illustrate the application of Bayesian methods to analyze dependent data. Pre-requisites: Module 2: Introduction to Clinical Trials I: Design or other introductory course on Bayesian statistics; familiarity with R/RStudio.