NSW Branch: October Event by Prof Elizabeth Stuart

  • 21 Oct 2019
  • 6:00 PM - 7:30 PM
Dealing with observed and unobserved effect moderators when estimating population average treatment effects

Many decisions in public health and public policy require estimation of population average treatment effects, including questions of cost effectiveness or when deciding whether to implement a screening program across a population. While randomized trials are seen as the gold standard for (internally valid) causal effects, they do not always yield accurate inferences regarding population effects. In particular, 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. 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. These sensitivity analyses are particularly crucial given the often limited data available from trials and on the population. 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. 

Biography

Elizabeth A. Stuart, Ph.D. is Professor in the Department of Mental Health at the Johns Hopkins Bloomberg School of Public Health, with joint appointments in the Department of Biostatistics and the Department of Health Policy and Management, and Associate Dean for Education at JHSPH. She received her Ph.D. in statistics in 2004 from Harvard University and is a Fellow of the American Statistical Association. Dr. Stuart has extensive experience in methods for estimating causal effects and dealing with the complications of missing data in experimental and non-experimental studies, particularly as applied to mental health, public policy, and education. She has published influential papers on propensity score methods and generalizing treatment effect estimate to target populations and taught courses and short courses on causal inference and propensity scores to a wide range of audiences. Her primary areas of application include mental health, substance use, and policy evaluation, including co-directing the JHSPH Center for Mental Health and Addiction Policy Research. She also serves as Evidence Workgroup lead for the Bloomberg American Health Initiative. Dr. Stuart has received research funding for her work from the National Institutes of Health, the US Institute of Education Sciences, and the National Science Foundation and has served on advisory panels for the National Academy of Sciences, the Patient Centered Outcomes Research Institute (PCORI), and the US Department of Education. She currently serves as Chair of the National Institute of Mental Health’s Services review panel (SERV). Dr. Stuart was recently recognized with the mid-career award from the Health Policy Statistics Section of the American Statistical Association, the Gertrude Cox Award for applied statistics, and the Myrto Lefkopoulou award from the Harvard University Department of Biostatistics.
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