This course introduces basic and advanced theory underlying propensity score analyses and provides practical insights into the conduct of studies employing the method. Course readings will include propensity score theory as well as applications. Lectures are complemented by computer lab sessions devoted to the mechanics of estimating and using the propensity score as a tool to control for confounding in observational research. Students should have knowledge in multivariable modeling approaches. A course project will involve the application of propensity scores to a data set or the review of a related, published paper.Course Activities: Lectures, readings, homeworks, computer labs, participation, project.
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Earlier Event: January 8
BEMC: Understanding Population-based Migraine through Genome-wide Genetics (Dan Chasman)
Later Event: February 5
BEMC: A New Approach to the Generalizability of Randomized Trials (Anders Huitfeldt)