Module dates/times: Monday, July 23; 8:30 a.m. -5 p.m.; Tuesday, July 24, 8:30 a.m.-5 p.m., and Wednesday, July 25, 8:30 a.m.-Noon
This course is full. If you wish to be placed on the waiting list, email firstname.lastname@example.org.
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.
Access 2017 Course Materials (2018 materials will be uploaded to this page prior to the start of the module)