Course overview

In the last two decades the Bayesian approach has become increasingly popular in virtually all application areas. The approach is especially known for its capability to tackle complex statistical modeling tasks. The aim of this course is to introduce the participants smoothly into Bayesian statistical methods, from basic concepts to hierarchical models, model building and model testing. Numerous biostatistical examples (e.g. meta-analyses, longitudinal studies including growth curve modelling, analysis of clinical trials, etc.) illustrate the theoretical concepts. The course is scheduled into classroom teaching and computer exercises, and uses the software packages WinBUGS, OpenBUGS, JAGS and but also their interfaces with R making use of R2WinBUGS, R2OpenBUGS and RJAGS. The course is based on a recently published Wiley book of Lesaffre and Lawson, entitled Bayesian Biostatistics. Each participant will receive a copy of this book, included in the course fee.

The course assumes a good knowledge of regression techniques (linear, logistic, etc.) and some knowledge of models for correlated data. Experience with R is beneficial though not essential; however programming skills are required for the course.