【学术讲堂】Assessing causal spillover effects in the mediation pathway analysis with areal data(宋学坤--密歇根大学)

发布者:统计与数据科学学院发布时间:2024-12-10浏览次数:10

专家简介】:宋学坤,密歇根大学安娜堡分校的生物统计学教授。他于1996年在加拿大不列颠哥伦比亚大学(温哥华)获得统计学博士学位。已发表超过230篇论文,培养了26名博士研究生,并指导了6名博士后研究员。他的研究兴趣包括数据整合、分布式推断、高维数据分析、纵向数据分析、中介效应分析以及时空建模。他是国际数理统计学会(IMS)、美国统计学会(ASA)Fellow以及国际统计学会(ISl) elected member。目前,他担任Journal of American Statistical Association、The Annals of Applied Statistics以及Journal of Multivariate Analysis的副主编。

报告摘要】:Mediation pathway analysis becomes rather complex when areal data are spatially correlated. This is because interference from neighboring locations emerges to produce spillover effects on outcomes of a target location. To assess such spillover effects, we proposed an extension of exposure mapping via the Spatial Structural Equation Model (RES-SEM). This modeling approach enables us to rigorously estimate how, and to what extent, neighboring exposures and mediators may influence outcomes at a target location. We establish key identifiability conditions for causal mediation and interference estimands which are estimated by the maximum likelihood estimation (MLE)established using the no-i.i.d. Theoretical guarantees are asymptotic theory. Our methodology is applied to analyze a county-level infectious disease model, examining the causal effect of political party affiliation on COVlD-19 mortality, mediated by vaccination hesitancy and compliance.

报告时间】:2024年12月16日 15:00-16:00

报告地点】:崇真楼110