Robust Regression Analysis for Clustered Interval-Censored Failure Time Data  

作　　者：LUO Lin ZHAO Hui 

机构地区：[1]School of Mathematics and Statistics,Central China Normal University,Wuhan 430079,China [2]School of Statistics and Mathematics,Zhongnan Univer'sity of Economics and Law,Wuhan 430064,China

出　　处：《Journal of Systems Science & Complexity》2021年第3期1156-1174,共19页系统科学与复杂性学报（英文版）

基　　金：supported by the National Natural Science Foundation of China under Grant Nos. 11471135and 11861030。

摘　　要：Clustered interval-censored failure time data often occur in a wide variety of research and application fields such as cancer and AIDS studies. For such data, the failure times of interest are interval-censored and may be correlated for subjects coming from the same cluster. This paper presents a robust semiparametric transformation mixed effect models to analyze such data and use a U-statistic based on rank correlation to estimate the unknown parameters. The large sample properties of the estimator are also established. In addition, the authors illustrate the performance of the proposed estimate with extensive simulations and two real data examples.

关 键 词：Clustered data interval-censoring random effects rank estimation semiparametric transformation models 

分 类 号：O212.1[理学—概率论与数理统计]