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A new approach to regression analysis of linear transformation model with interval-censored 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, Peoples R China.
[Zhao, Hui] Zhongnan Univ Econ & Law, Sch Stat & Math, Wuhan 430073, Peoples R China.
通讯机构:
[Zhao, Hui] Z
Zhongnan Univ Econ & Law, Sch Stat & Math, Wuhan 430073, Peoples R China.
语种:
英文
关键词:
Estimating equation;propensity score;linear transformation model;interval-censored data
期刊:
Communications in Statistics - Theory and Methods
ISSN:
0361-0926
年:
2023
卷:
52
期:
15
页码:
5470-5482
基金类别:
The research was partially supported by National Natural Science Foundation of China (Grant Nos. 12171483, 11861030). The authors wish to thank the Editor, the Associate Editor and two reviewers for their many helpful and insightful comments and suggestions that greatly improved the paper.
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:
Interval-censored failure time data often occur in medical follow-up studies among other areas. Regression analysis of linear transformation models with interval-censored data has been investigated by several authors under different contexts, but most of the existing methods assume that the covariates are discrete because these methods rely on the estimation of conditional survival distribution function. Without this assumption, this paper constructs a new generalized estimating equation using the propensity score. The proposed inference procedure does not need to estimate the conditional surv...

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