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
