报告人：彭梦姣 助理教授
主持人：张日权 华东师范大学教授、统计学院院长
时 间：2020年10月14日（周三）下午14:00-15:00
地 点：中北校区理科大楼A1716室
题 目：Analysis of complex survival data subject to semi-competing risks
摘要：In this talk, I will introduce my past and recent work in the analysis of complex survival data subjectto semi-competing risks. Semi-competing risks data is a type of survival data including multiplesurvival endpoints, which is quite common in medical research and clinical trials for assessingtreatment efficacy and disease progression. In the work to analyze clustered endpoints with semicompeting risks via a flexible semiparametric modeling framework,we develop a nonparametricmaximum likelihood estimation procedure via a Monte Carlo EM algorithm, and establish desirableasymptotic properties of the resulting estimators. In the study of multiple time-to-event endpointssubject to two sets of semi-competing risks, we propose a novel statistical approach that jointlymodels such data via a pair of copulas to account for multiple dependence structures, and develop apseudo-likelihoodestimationprocedure.Wealsoproposetwomodel-freefeaturescreeningmethods to select the important features for semi-competing risks data, which are often collectedwith ultrahigh-dimensional gene features in modern cancer studies. Extensive simulation studieshave been carried out and resultsshow promising finite sample performance of all proposedmethods. Analysis of real data sets from various medical studies demonstrate the practical utility ofour proposed methods.
