A semiparametric linear transformation model for general biased-sampling and right-censored data

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	A semiparametric linear transformation model for general biased-sampling and right-censored data
	Wei, Wenhua 1,4; Zhou, Yong2,5 ; Wan, Alan T. K.3,6
	2019
发表期刊	STATISTICS AND ITS INTERFACE
ISSN	1938-7989
卷号	12 期号:1 页码:77-92
摘要	The semiparametric linear transformation (SLT) model is a useful alternative to the proportional hazards ([9]) and proportional odds ([4]) models for studying the dependency of survival time on covariates. In this paper, we consider the SLT model for biased-sampling and right-censored data, a feature commonly encountered in clinical trials. Specifically, we develop an unbiased estimating equations approach based on counting process for the simultaneous estimation of unknown coefficients and handling of sampling bias. We establish the consistency and the asymptotic normality of the proposed estimator, and provide a closed form expression for the estimator's covariance matrix that can be consistently estimated by a plug-in method. In a simulation study, we compare the finite sample properties of the proposed estimator with those of existing methods that either assumes that the sampling bias is of the length-bias type, or ignores the sampling bias altogether. The proposed method is further illustrated by two real clinical datasets.
关键词	Biased-sampling Estimating equation Right-censoring Semiparametric linear transformation model
语种	英语
资助项目	Shanghai University of Finance and Economics[2017110070] ; State Key Program in the Major Research Plan of National Natural Science Foundation of China[91546202] ; State Key Program of National Natural Science Foundation of China[71331006] ; Innovative Research Team of Shanghai University of Finance and Economics[IRTSHUFE13122402] ; Theme-Based Research Scheme from the Hong Kong Research Grants Council[T32-102/14N] ; General Research Fund from the Hong Kong Research Grants Council[9042086] ; City University of Hong Kong[7004786]
WOS研究方向	Mathematical & Computational Biology ; Mathematics
WOS类目	Mathematical & Computational Biology ; Mathematics, Interdisciplinary Applications
WOS记录号	WOS:000460758600008
出版者	INT PRESS BOSTON, INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/33450
专题	应用数学研究所
通讯作者	Wei, Wenhua
作者单位	1.Shanghai Univ Finance & Econ, Shanghai, Peoples R China 2.Acad Math & Syst Sci, Beijing, Peoples R China 3.City Univ Hong Kong, Hong Kong, Peoples R China 4.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China 5.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 6.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Wei, Wenhua,Zhou, Yong,Wan, Alan T. K.. A semiparametric linear transformation model for general biased-sampling and right-censored data[J]. STATISTICS AND ITS INTERFACE,2019,12(1):77-92.
APA	Wei, Wenhua,Zhou, Yong,&Wan, Alan T. K..(2019).A semiparametric linear transformation model for general biased-sampling and right-censored data.STATISTICS AND ITS INTERFACE,12(1),77-92.
MLA	Wei, Wenhua,et al."A semiparametric linear transformation model for general biased-sampling and right-censored data".STATISTICS AND ITS INTERFACE 12.1(2019):77-92.