学术讲座

12月19日 | Menggang Yu Entropy Balancing for Causal Generalization with Target Sample Summary Information

时   间🤽🏻‍♂️🕵🏼:2023年12月19日 15:00-16:00

地   点: 普陀校区理科大楼A1716

报告人:Menggang Yu  密西根大学安娜堡分校教授

主持人:徐进 上海光辉平台娱乐教授

摘   要:

In this talk, we focus on estimating the average treatment effect (ATE) of a target population when individual-level data from a source population and summary-level data (e.g., first or second moments of certain covariates) from the target population are available. In the presence of heterogeneous treatment effect, the ATE of the target population can be different from that of the source population when distributions of treatment effect modifiers are dissimilar in these two populations, a phenomenon also known as covariate shift. Many methods have been developed to adjust for covariate shift, but most require individual covariates from a representative target sample. We develop a weighting approach based on summary-level information from the target sample to adjust for possible covariate shift in effect modifiers. In particular, weights of the treated and control groups within a source sample are calibrated by the summary-level information of the target sample. Our approach also seeks additional covariate balance between the treated and control groups in the source sample.

报告人简介🫱🏻:

Dr. Menggang Yu is a professor at the Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison and Director of the Biostatistics Shared Resources at the UW Carbone Cancer Center. He is an elected fellow of the American Statistical Association (ASA). From 1/1/2024, Dr. Yu will join the University of Michigan as a faculty member at the Department of Biostatistics.

Dr. Yu conducts broad statistical methodology research, all motivated by his daily collaborative experience with medical investigators. His publications cover extensive topics including joint modeling of longitudinal and survival data, missing data, clinical trial design and analysis, causal inference, and personalized medicine. Dr. Yu is also a devoted statistical collaborator. His scientific collaboration is mainly in the areas of cancer and health care research.



发布者:张瑛发布时间:2023-12-18浏览次数:88

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