Bayesian Thinking and Methods

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 and for providing an intuitive outcome of the statistical analysis. In Session 1, Bayes Theorem will be explained using a simple illustration. The construction of the prior distribution and the computation of the posterior distribution will then be illustrated using a variety of examples. In Session 2, we indicate the popularity of the Bayesian approach in various research areas, not only medical areas. In Session 3, we show the application and usefulness of the Bayesian approach in the area of randomized clinical trials. The ultimate aim of this crash course is to introduce the participants smoothly into Bayesian statistical methods and trigger them to apply them in practice. The course is partly based on the Wiley book of Lesaffre and Lawson, published in 2012 and entitled: Bayesian Biostatistics and the Chapman & Hall edited book Bayesian Methods in Pharmaceutical Research by E. Lesaffre, G, Baio and B. Boulanger published in 2020.
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