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Department of Epidemiology Seminar Series: Dr. Erin Hartman - Covariate Selection for Generalizing Experimental Results

Department of Epidemiology Seminar Series: Dr. Erin Hartman - Covariate Selection for Generalizing Experimental Results

Date 
Wednesday, February 20, 2019 - 12:00pm to 1:00pm
Location 
33-105 CHS Los Angeles , CA
California US
Featuring 
Dr. Erin Hartman, PhD, MA, MA
Event Contact 

Taylor Mobley

tmmobley@ucla.edu

Dr. Erin Hartman, PhD, MA, MA

Abstract:

Researchers are often interested in generalizing the average treatment effect (ATE) estimated in a randomized experiment to non-experimental target populations. Previous studies have shown that an unbiased estimate for the population ATE can be obtained if selection into the experiment is independent of treatment heterogeneity given a set of variables researchers adjust for. Although this separating set has simple mathematical representation, it is often unclear how to select this set in practice. In this talk, we propose a data-driven method to estimate the minimum separating set. Our approach has two advantages. First, because we find a separating set of the smallest size, it is easier for researchers to measure it in the target population. Second, our algorithm can incorporate researcher-specific data constraints. When they know certain variables are unmeasurable in the target population, our method can identify a minimal separating set subject to such constraints, if one is feasible. We validate our proposed method using naturalistic simulations.

 

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