Module dates/times: Wednesday, July 10, 1:30-5 p.m.; Thursday, July 11, 8:30 a.m.-5 p.m., and Friday, July 12, 8:30 a.m.-5 p.m.

Prerequisites: This module assumes knowledge of the material in Module 1: Probability and Statistical Inference, though not necessarily from taking that module. A working knowledge of R or SAS would be helpful.

This module provides an introduction to causal inference. Topics to be covered include potential outcomes, directed acyclic graphs, confounding, g-methods, instrumental variables, mediation, principal stratification, and interference. The methods will be illustrated using infectious disease examples, with analysis carried out in SAS and/or R.