统计与管理学院2016年学术报告第29期

【主  题】Analysis of  Longitudinal Survival Data with Multiple Features: A Case Study

【报告人】 鹿涛 博士

纽约州立大学阿巴里分校

【时  间】 2016年6月17日（星期五）15:00－16:00

【地  点】 上海财经大学统计与管理学院大楼1208室

【摘  要】Longitudinal survival data are often collected from clinical studies. Mixed-effects joint models are commonly used for the analysis of such data. Nevertheless, the following issues may arise in longitudinal survival data analysis: (i) most joint models assume a simple parametric mixed-effects model for longitudinal outcome, which may obscure the important relationship between response and covariates; (ii) clinical data often exhibits asymmetry so that symmetric assumption for model errors may lead to biased estimation of parameters; (iii) response may be missing and missingness  may be informative. There is little work concerning all of these issues simultaneously. Motivated by an AIDS clinical data, we develop a Bayesian varying coefficient mixed-effects joint model with skewness and missingness to study the simultaneous influence of these features.

【邀请人】 张志远