This module has reached capacity and is now closed. 

Live session timeframe (exact schedule with live sessions will be posted by module instructors prior to the start of the module): Wednesday: 11:30 a.m.-2:30 p.m. Pacific (2:30-5:30 p.m. Eastern); Thursday, 8 a.m. – 2:30 p.m. Pacific  (11 a.m. – 5:30 p.m. Eastern); Friday, 8 a.m. – 2:30 p.m. Pacific (11 a.m. – 5:30 p.m. Eastern).

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.