33rd International Summer School of Epidemiology

 

COURSE 2: Introduction to g-methods for causal inference

Jessie K. Edwards

This course builds on basic epidemiologic principles to introduce a suite of “generalized” methods for causal inference from observational data. Specifically, the course will introduce potential outcomes, discuss the components of a causal question, describe inverse probability weighting and g-computation for the estimation of causal effects and discuss specific methods to address various sources of bias within the causal framework. Each session will consist of both lecture and practice-based laboratory components. The course is targeted to students who have previously taken introductory courses in epidemiologic methods, have familiarity with the basics of probability and statistics and have some experience with data analysis.