时 间：2020年7月6日 09:00-11:30 (I)
2020年7月7日 08:30-11:30 (II)
2020年7月8日 08:30-11:30 (III)
方 式：上海市教育云直播平台
直播链接：http://zhibo.shec.edu.cn/golive/hsd
主讲人：林丹瑜
主持人：周迎春、方 方、於州
摘要：
In many scientific studies, the outcomeof interest is the time to the occurrence of a particular event, such as diseaseor death. A common complication with such data is that some study participantshave not experienced the event of interest by the end of the study such thattheir even times are censored. Special statistical methods have been developedto provide valid and efficient analysis of potentially censored event time data.This short course will offer an overview of these methods, focusing on thecommonly used Kaplan-Meier estimator, log-rank test, and Cox proportionalhazards model. We will study the theoretical properties of these methodsthrough the counting-process martingale theory and address practical issues inthe applications of these methods, including sample size determination,variable selection, and model checking. Relevant software will be described.Detailed illustrations with real data will be provided.
个人简介：
Danyu Lin is the Dennis GillingsDistinguished Professor of Biostatistics at the University of North Carolina atChapel Hill. Professor Lin is an internationally renowned expert in survival analysis.He has published over 200 peer-reviewed papers, most of which appeared in topstatistical journals. Several of his methods have been incorporated into majorsoftware packages, such as SAS, R and STATA, and widely used in practice.Professor received the Mortimer Spiegelman Gold Medal from the American PublicHealth Association in 1999 and the George W. Snedecor Award from the Committeeof Presidents of Statistical Societies in 2015. He is a Fellow of both theAmerican Statistical Association and the Institute of Mathematical Statistics.He currently serves as an Associate Editor of Biometrika and Journal of theAmerican Statistical Association.