Event

Determining “what works for whom” is a key goal in prevention and treatment across a variety of areas, including mental health.  Identifying effect moderators—factors that relate to the size of treatment effects--is crucial for delivery of treatment and prevention interventions, but doing so is incredibly difficult using standard study designs. Randomized trials, the gold standard for estimating average effects, are typically under-powered to detect moderation. Large-scale nonexperimental studies may provide another way to examine effect moderation, but can suffer from confounding.

This talk will describe recent machine learning and Bayesian methods advances to combine randomized trials and electronic health record (EHR) data to examine effect heterogeneity.  We present results from simulation studies comparing a set of recently proposed methods for combining data sources, with the goal of estimating conditional average treatment effects.  We also provide initial application of the methods to data from randomized trials and electronic health record data of individuals receiving medication treatment for major depressive disorder.

Elizabeth A. Stuart, Ph.D. is the Frank Hurley and Catharine Dorrier Chair and Bloomberg Professor of American Health in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, with joint appointments in the Department of Mental Health and the Department of Health Policy and Management.  A statistician by training, her research interests are in design and analysis approaches for estimating causal effects in experimental and non-experimental studies, including questions around the external validity of randomized trials and the internal validity of non-experimental studies.  Her recent interests include combining data sources to assess treatment effect heterogeneity and methods for evidence synthesis.  She has extensive experience with the application of causal inference methods in education, the social sciences, and public health, particularly mental health, substance use, and state policy evaluation. She has received research funding for her work from the National Science Foundation, the Institute of Education Sciences, the WT Grant Foundation, and the National Institutes of Health and has served on advisory panels for the National Academy of Sciences,  the US Department of Education, and the Patient Centered Outcomes Research Institute.  She received the mid-career award from the Health Policy Statistics Section of the ASA, the Gertrude Cox Award for applied statistics, Harvard University’s Myrto Lefkopoulou Award for excellence in Biostatistics, and the Society for Epidemiologic Research Marshall Joffe Epidemiologic Methods award.

This seminar will be held via Zoom and is being recorded.

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Meeting ID: 841 2920 2481

Passcode: 379685