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The Proportional Mean Residual Life Regression Model with Cure Fraction and Auxiliary Covariate

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成果类型:
期刊论文
作者:
Jin, Shao-jia;Liu, Yan-yan;Mao, Guang-cai;Shan, Ming-yu
通讯作者:
Mao, GC
作者机构:
[Shan, Ming-yu; Jin, Shao-jia; Liu, Yan-yan] Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China.
[Mao, Guang-cai] Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Peoples R China.
通讯机构:
[Mao, GC ] C
Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
auxiliary covariate;Kernel smoothing;logistic regression;mean residual life;mixture cure model
期刊:
应用数学学报:英文版
ISSN:
0168-9673
年:
2022
卷:
38
期:
2
页码:
312-323
基金类别:
This paper is supported by the National Natural Science Foundation of China (No. 11971362, 12101256). Acknowledgments
机构署名:
本校为通讯机构
院系归属:
数学与统计学学院
摘要:
As biological studies become more expensive to conduct, it is a frequently encountered question that how to take advantage of the available auxiliary covariate information when the exposure variable is not measured. In this paper, we propose an induced cure rate mean residual life time regression model to accommodate the survival data with cure fraction and auxiliary covariate, in which the exposure variable is only assessed in a validation set, but a corresponding continuous auxiliary covariate is ascertained for all subjects in the study cohort. Simulation studies elucidate the practical per...

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