EPID733: Quasi-experimental Methods In Epidemiology
Graduate level
Residential
Summer term(s) for residential students;
1 credit hour(s) for residential students;
Instructor(s): Staff (Residential);
Prerequisites: No
Advisory Prerequisites: familiarity with introductory epidemiology (e.g., confounding), and introductory biostatistics (e.g., expectation, laws of probability, linear regression); and some background in either Stata or R.
Description: The course will cover the concepts, assumptions, statistical techniques, and empirical applications of these methods in the literature. Upon completion of the course, students will be able to critique the quality of a research paper that uses these methods and be able to conduct basic analyses in Stata or R.
Learning Objectives: Currently, the cluster on causal inference at SSE includes full courses on causal inference fundamentals, mediation analysis, sensitivity analysis, and machine learning. However, there is no systematic coverage on 1) instrumental variable analysis, 2) difference-in-differences methods, and 3) regression discontinuity design. This proposed course will fill in this gap. These tools have found
