Thursday, October 9th
11:45am - 1:00pm, Zoom
Meeting ID: 963 2560 9671
Passcode: 698339
KC Gary Chan, PhD
Professor, Health Services; Professor, Biostatistics
University of Washington School of Public Health
Robust and Efficient Semiparametric Inference for the Stepped Wedge Design
Stepped wedge designs (SWDs) are increasingly used to evaluate longitudinal cluster-level interventions but pose substantial challenges for valid inference. Because crossover times are randomized, intervention effects are intrinsically confounded with secular time trends, while heterogeneous cluster effects, complex correlation structures, baseline covariate imbalances, and unreliable standard errors from few clusters further complicate statistical inference. We propose a unified semiparametric framework for estimating possibly time-varying intervention effects in SWDs that directly addresses these issues. A nonstandard development of semiparametric efficiency theory is required to accommodate correlated observations within clusters, non-identically distributed outcomes across clusters due to varying cluster-period sizes, and weakly dependent treatment assignments that are hallmarks of SWDs. The resulting estimator of treatment contrast is consistent and asymptotically normal even under misspecification of the covariance structure and control cluster-period means, and achieves the semiparametric efficiency bound when both are correctly specified. To facilitate inference for trials with few clusters, we introduce a permutation-based procedure to better capture finite-sample variability and a leave-one-out correction to mitigate plug-in bias. We further discuss how effect modification can be naturally incorporated, and imbalanced precision variables can be accommodated via a simple adjustment closely related to post-stratification, a novel connection of independent interest. Simulations and application to a public health trial demonstrate the robustness and efficiency of the proposed method relative to standard approaches.
Biostatistics Departmental Seminars & Lectures
During the Fall and Spring semesters, the Department of Biostatistics holds regular seminars on Thursdays, called the Levin Lecture Series, on a wide variety of topics which are of interest to both students and faculty. Over each semester, there are also often guest lectures outside the regular Thursday Levin Lecture Series, to provide a robust schedule the covers the wide range of topics in Biostatistics. The speakers are invited guests who spend the day of their seminar discussing their research with Biostatistics faculty and students.
