Propensity Score and Related Methods for Estimating Causal Effects

1 Credit.

Discusses the importance of the careful design of non-experimental studies, and the role of propensity scores and related methods in that design, with the main goal of providing practical guidance on use of sample equating methods. Covers the primary ways of using propensity scores and related methods to adjust for confounders when estimating the effect of a particular “cause” or “intervention,” including weighting, subclassification, and matching. Examines issues such as how to specify and estimate a propensity score model, selecting covariates to include in the model, and diagnostics. Draws examples from across public health. Emphasizes non-experimental studies; however, also discusses applications to randomized trials such as examining levels of adherence and generalizability.