时 间：2023年11月29日 9:30-10:30
地 点：腾讯会议ID：816-652-567
报告人：胡涛 首都师范大学教授
主持人：马慧娟 华东师范大学副教授
摘 要：
Mixed panel count data have attracted increasing attention in medical research based on event history studies. When such data arise, one either observes the number of event occurrences or only knows whether the event has happened or not over an observation period. In this article, we discuss variable selection in event history studies given such complex data, for which there does not seem to exist an established procedure. For the problem, we propose a penalized likelihood variable selection procedure and for the implementation, an expectation–maximization algorithm is developed with the use of the coordinate descent algorithm in the M-step. Furthermore, the oracle property of the proposed method is established, and a simulation study is performed and indicates that the proposed method works well in practical scenarios. Finally, the method is applied to identify the risk factors associated with medical non-adherence arising from the Sequenced Treatment Alternatives to Relieve Depression Study.
报告人简介：
胡涛，首都师范大学数学科学学院，教授、博士生导师。研究方向：生物统计、应用统计。2009年毕业于北京师范大学数学科学学院，获概率论与数理统计专业博士学位。美国University of Missouri 统计系博士后。2009年3月至2012年12月先后在新加坡国立大学统计与应用概率系、南洋理工大学数学与物理学院任Research Assistant 和Research Fellow。2018年入选北京市优秀人才培养资助青年拔尖个人项目和北京市市属高校高水平教师队伍建设支持计划青年拔尖人才培育项目，曾获国家统计局第十届全国统计科研优秀成果奖一等奖。在国内外学术刊物Journal of the American Statistical Association、Biometrika、Renewable Energy、Energy Conversion and Management、中国科学：数学等上发表学术论文多篇。兼任全国工业统计学教学研究会副会长、北京应用统计学会副会长、中国现场统计研究会理事、中国数学会概率统计分会理事、中国数学会数学教育分会常务理事。