American Statistical Association
New York City
Metropolitan Area Chapter

Levin Lecture Series: Spring 2019 Colloquium Seminars
Department of Biostatistics
Mailman School of Public Health
Columbia University



SENSITIVITY ANALYSES FOR UNOBSERVED EFFECT MODERATION
WHEN GENERALIZING FROM TRIAL TO POPULATION

by

Elizabeth Stuart
Professor
Department of Mental Health & Department of Biostatistics
Johns Hopkins Bloomberg School of Public Health

Host: Dr. Christina Mauro


Abstract

In the presence of treatment effect heterogeneity, the average treatment effect (ATE) in a randomized controlled trial (RCT) may differ from the average effect of the same treatment if applied to a target population of interest. But for policy purposes we may desire an estimate of the target population ATE. If all treatment effect moderators are observed in the RCT and in a dataset representing the target population, then we can obtain an estimate for the target population ATE by adjusting for the difference in the distribution of the moderators between the two samples. However, that is often an unrealistic assumption in practice. This talk will discuss methods for generalizing treatment effects under that assumption, as well as sensitivity analyses for two situations: (1) where we cannot adjust for a specific moderator observed in the RCT because we do not observe it in the target population; and (2) where we are concerned that the treatment effect may be moderated by factors not observed even in the RCT. Outcome-model and weighting-based sensitivity analysis methods are presented. The methods are applied to examples in drug abuse treatment. Implications for study design and analyses are also discussed, when interest is in a target population ATE.


Date: Thursday, May 2, 2019
Time: 11:45 A.M. - 12:45 P.M.
Location: Mailman School of Public Health
Department of Biostatistics
722 West 168th Street
AR Building
8th Floor Auditorium
New York, New York

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