Empirical Bayes

Time:  2:00 PM to 3:00 PM ET

Series: HERC Econometrics with Observational Data

Speaker: David Chan, MD, PhD

Description:  This seminar will provide an introduction to empirical Bayes. When we have a finite sample of observations and increasingly rich covariates, empirical Bayes provides a useful tool to form better policy-relevant predictions than those from standard regression methods. We will discuss the rationale behind empirical Bayes, connections with the machine learning literature, and illustrative examples from the applied economics literature.

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.

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