Causal Inference in Epidemiology: Recent Methodological Developments

Program type: 
Program description: 

Course date: 5 days in November

Causal inference is a central aim of many empirical investigations, and arguably most studies in the fields of medicine, epidemiology and public health.

This course will discuss the current state of the art with respect to these issues, while retaining a practical focus. The potential outcomes framework, causal diagrams, standardization, propensity scores, inverse probability weighting, instrumental variables, marginal structural models, causal mediation analysis and examples of sensitivity analysis will be discussed. Participants will acquire awareness of the common threads across these new methods and competence in applying them in simple settings.

Program discipline(s): 
Global health
Public health
Epidemiology
Statistics