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Robust Regression Analysis for Clustered Interval-Censored Failure Time Data

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成果类型:
期刊论文
作者:
Luo Lin;Zhao Hui*
通讯作者:
Zhao Hui
作者机构:
[Luo Lin] Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Peoples R China.
[Zhao Hui] Zhongnan Univ Econ & Law, Sch Stat & Math, Wuhan 430064, Peoples R China.
通讯机构:
[Zhao Hui] Z
Zhongnan Univ Econ & Law, Sch Stat & Math, Wuhan 430064, Peoples R China.
语种:
英文
关键词:
Clustered data;interval-censoring;random effects;rank estimation;semiparametric transformation models
期刊:
系统科学与复杂性(英文版)
ISSN:
1009-6124
年:
2021
卷:
34
期:
3
页码:
1156-1174
基金类别:
This paper was supported by the National Natural Science Foundation of China under Grant Nos. 11471135 and 11861030.
机构署名:
本校为第一机构
院系归属:
数学与统计学学院
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 estim...

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