Time-varying latent model for longitudinal data with informative observation and terminal event times  

作　　者：PEI YanBo DU Ting SUN LiuQuan 

机构地区：[1]School of Statistics,Capital University of Economics and Business,Beijing 100070,China [2]Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China

出　　处：《Science China Mathematics》2016年第12期2393-2410,共18页中国科学：数学（英文版）

基　　金：supported by National Natural Science Foundation of China (Grant Nos. 11231010, 11171330 and 11201315);Key Laboratory of Random Complex Structures and Data Science, Chinese Academy of Sciences (Grant No. 2008DP173182);Beijing Center for Mathematics and Information Interdisciplinary Sciences

摘　　要：Longitudinal data often occur in follow-up studies, and in many situations, there may exist informative observation times and a dependent terminal event such as death that stops the follow-up. We propose a semiparametric mixed effect model with time-varying latent effects in the analysis of longitudinal data with informative observation times and a dependent terminal event. Estimating equation approaches are developed for parameter estimation, and asymptotic properties of the resulting estimators are established. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a bladder cancer study is provided.Longitudinal data often occur in follow-up studies, and in many situations, there may exist informative observation times and a dependent terminal event such as death that stops the follow-up. We propose a semiparametric mixed effect model with time-varying latent effects in the analysis of longitudinal data with informative observation times and a dependent terminal event. Estimating equation approaches are developed for parameter estimation, and asymptotic properties of the resulting estimators are established. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a bladder cancer study is provided.

关 键 词：estimating equations informative observation times joint modeling longitudinal data terminal event time-varying effect 

分 类 号：O212.1[理学—概率论与数理统计]