报告人：孙六全
报告地点：数学与统计学院四楼报告厅
报告时间：2019年10月24日星期四16:00-17:00
报告摘要：
In many medical studies, markers are contingent on recurrent events and the cumulative markers are usually of interest. However, the recurrent event process is often interrupted by a dependent terminal event, such as death. In this article, we propose a joint modeling approach for analyzing marker data with informative recurrent and terminal events. This approach introduces a shared frailty to specify the explicit dependence structure among the markers, the recurrent and terminal events. Estimation procedures are developed for the model parameters and the degree of dependence, and the asymptotic properties of the proposed estimators are established. In addition, a prediction of the covariate-specific cumulative markers is provided. The finite sample performance of the proposed estimators is examined through simulation studies. An application to a medical cost study of chronic heart failure patients from the University of Virginia Health System is illustrated.
主讲人简介：
中国科学院数学与系统科学研究院研究员、博士生导师,中科院数学院统计中心副主任。中科院数学院十大突出科研成果奖获得者，部分工作入选为中科院数学院十大重要科研进展。先后主持或主要参加了973重大项目，国家自然科学基金重大项目、重点项目和面上项目等18项。孙六全教授长期从事各种复杂删失数据的理论与方法研究，特别是生物和医学数据的建模与统计推断，包括复杂纵向数据、复发事件数据以及各种不完全删失数据下统计分析，提出了一系列新的建模方法和估计方法，获得了许多深刻的重要成果。在国内外核心刊物发表学术论文130余篇，包括统计顶级杂志JASA和Biometrika 8篇。已被SCI收录90多篇，EI收录9篇，美国Math. Review收录110余篇。论文被他人引用400多次，其中被SCI他引300多次，被Springer出版三本英文专著他引20多次。在国际学术会议上多次作特邀报告。
