Module date/time: Thursday, July 26, 8:30 a.m.-5 p.m.
This module provides an introduction to Bayesian methods for biomedical research. Specifically, we discuss the Bayesian paradigm introducing the subjective interpretation of probability; Bayes Theorem; and prior, posterior and predictive distributions. We contrast the Bayesian and frequentist approaches using simple biomedical problems including diagnostic testing and design and monitoring of clinical trials, among others.
This module uses a number of R packages to illustrate the application of Bayesian methods to analyze independent data.
Pre-requisite: introductory course in statistics/biostatistics; linear regression; familiarity with R/RStudio.
Access 2017 Course Materials (2018 materials will be uploaded to this page prior to the start of the module)