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.