讲座题目：Data integration with oracle use of external summary information from heterogeneous populations

主 讲 人：Assoc. Prof. Peisong Han

讲座时间：2022年6月26日（周日）上午9:00-10:30

地点：腾讯会议 ID 270-827-128

主讲人简介：

Peisong Han is Associate Professor in the Department of Biostatistics at the University of Michigan. He obtained his PhD in Biostatistics from the University of Michigan in 2013. His primary research interests include (i) missing data and biased sampling problems in public health studies and survey sampling, (ii) data integration, especially when summary information is available for some studies and individual-level data are available for others, and (iii) longitudinal (correlated/clustered) data analysis. He is an Associate Editor for Biometrics.

讲座摘要：

It is common to have access to summary information from external studies. Such information can be useful in model building for an internal study of interest and can improve parameter estimation efficiency when incorporated. However, external studies may target populations different from the internal study, in which case an incorporation of the corresponding summary information may introduce estimation bias. We develop a method that selects the external studies whose target population is the same as the internal study and simultaneously incorporates their available information into estimation. The resulting estimator has the efficiency as if we knew which external studies target the same population and made use of information from those studies alone. The method is applied to a prostate cancer study to incorporate external summary information to improve parameter estimation.