Understanding causation with observational data is often more dependent on what we don’t observe than what we do observe. Multivariate techniques can be very useful for understanding observed characteristics. Propensity scores have emerged over the past 20 years as another way to control for observables. We describe the concepts behind propensity scores and how they have been used (and misused) in practice. Finally, we work through an example using propensity scores.
Target Audience: Researchers who would like an introduction to econometric methods for observational studies in health services research. Seminar material will assume knowledge of basic probability and statistics and familiarity with linear regression.