KMS Of Academy of mathematics and systems sciences, CAS
| A semiparametric linear transformation model for general biased-sampling and right-censored data | |
Wei, Wenhua1,4; Zhou, Yong2,5 ; Wan, Alan T. K.3,6
| |
| 2019 | |
| Source Publication | STATISTICS AND ITS INTERFACE
 |
| ISSN | 1938-7989 |
| Volume | 12Issue:1Pages:77-92 |
| Abstract | 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. |
| Keyword | Biased-sampling Estimating equation Right-censoring Semiparametric linear transformation model |
| Language | 英语 |
| Funding Project | 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 Research Area | Mathematical & Computational Biology ; Mathematics |
| WOS Subject | Mathematical & Computational Biology ; Mathematics, Interdisciplinary Applications |
| WOS ID | WOS:000460758600008 |
| Publisher | INT PRESS BOSTON, INC |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/33450 |
| Collection | 应用数学研究所 |
| Corresponding Author | Wei, Wenhua |
| Affiliation | 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 |
| Recommended Citation 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. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment