报告题目：Group inference for high-dimensional mediation models

报告人：罗珊（上海交通大学）

报告时间：2023年5月19日上午10：00-11：00

报告地点：腾讯会议465-659-976

摘要：Causal mediation analysis is a fundamental statistical approach to understanding the effect of exposure on an outcome. In this paper, we investigate group inference for high-dimensional mediation models by considering the mediators in an interested group jointly or individually. For both situations, we construct suitable test statistics and establish their asymptotic distributions. A simple estimator for the joint group indirect effect is also introduced. Its asymptotic normality is also established. Extensive numerical studies demonstrate that our proposed methods outperform recent representative approaches. We also apply our methods to analyse how DNA methylation operates in the regulation of human stress reactivity impacted by childhood trauma.

报告人简介：

罗珊，新加坡国立大学统计学博士，密歇根大学生物统计系访问学者。现为上海交通大学数学科学学院长聘副教授。主要研究领域为高维数据中的模型选择标准和变量选择方法。文章主要发表在Journal of the American Statistical Association，Statistica Sinica，Journal of Multivariate Analysis，Sankhya A, Annals of the Institute of Statistical Mathematics，Computational Statistics and Data Analysis, Journal of Statistical Planning and Inference等期刊上。