数学与统计学院学术报告[2021] 078号

(高水平大学建设系列报告578号)

报告题目: Causal Mediation Analysis with Latent Mediators and Survival Outcome

报告人：宋心远教授（香港中文大学）

报告时间：2021年9月3日上午11:00-12:00　　　　　　　　　　　　　 　　

报告地点： 汇星楼501　　　　　　　　　　　　　　　　　　　　

报告内容：This study develops a joint modeling approach that incorporates latent traits into causal mediation analysis with multiple mediators and a survival outcome. A linear structural equation model is used to characterize the latent mediators with several highly correlated observable surrogates and depicts the relationships among multiple parallel or causally ordered mediators and the exposure. A proportional hazards model is used to derive the path-specific causal effects on the scale of hazard ratio under the counterfactual framework with a set of sequential ignorability assumptions. A Bayesian approach with Markov chain Monte Carlo algorithm is developed to perform efficient estimation of the causal effects. Posterior propriety theory is established for the proportional hazards model with latent variables. Empirical performance of the proposed method is verified through simulation studies. The proposed model is then applied to a study on the Alzheimer's Disease Neuroimaging Initiative dataset to investigate the causal effects of APOE-epsilon4 allele on the disease progression, either directly or through potential mediators, such as hippocampus atrophy, ventricle expansion, and cognitive impairment.

报告人简历: 宋心远，香港中文大学教授，主要研究方向包括潜变量模型，非参数和半参数回归，贝叶斯方法，生存分析及统计诊断等。宋心远教授于2000年在香港中文大学获得统计学博士学位，2001-2003年在中文大学从事统计博士后研究，2004年到至今任中文大学助理教授，副教授，教授。迄今为止,在国际著名的统计学及应用数学类期刊发表100多篇高水平学术论文。担任或曾经担任《Biometrics》、《Psychometrika》、《Structural Equation Modeling - A Multidisciplinary Journal》、《Computational Statistics and Data Analysis》、《Journal of the Korean Statistical Society》及《Statistical Theory and Related Fields》等多个国际期刊的副主编及编委。

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数学与统计学院

2021年9月1日