Prerequisite
Statistics (preferably at the graduate level)
Description
Introduces quantitative (econometric) methods frequently used in health systems research, as well as in applied health economics and health policy. In many applications, researchers want to understand a process by which data and outcomes are generated; however, many data generating processes (DGPs) are possible given observed data. This course deals with how to determine which DGPs, and hence which “story”, has generated your data. The course uses applications of statistical tests and procedures in the context of distinguishing between models and explores the applications of a range of frameworks to the types of questions addressed by social scientists and health services researchers. It is assumed that students have basic (graduate) training in statistics.
Instructor
Evaluation
- Three Assignments (20% each)
- 60%
- Major Paper or Referee Reports (MSc only)
- 40%