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Power-transformed linear regression on quantile residual life for censored competing risks data
Fan, Caiyun1,2; Zhang, Feipeng3; Zhou, Yong2,4
2016
Source PublicationCOMMUNICATIONS IN STATISTICS-THEORY AND METHODS
ISSN0361-0926
Volume45Issue:20Pages:5884-5905
AbstractThis paper proposes a power-transformed linear quantile regression model for the residual lifetime of competing risks data. The proposed model can describe the association between any quantile of a time-to-event distribution among survivors beyond a specific time point and the covariates. Under covariate-dependent censoring, we develop an estimation procedure with two steps, including an unbiased monotone estimating equation for regression parameters and cumulative sum processes for the Box-Cox transformation parameter. The asymptotic properties of the estimators are also derived. We employ an efficient bootstrap method for the estimation of the variance-covariance matrix. The finite-sample performance of the proposed approaches are evaluated through simulation studies and a real example.
KeywordBox-Cox transformation Competing risks Empirical process Quantile residual life 62N01 62N02
DOI10.1080/03610926.2014.950873
Language英语
Funding ProjectGraduate Creation Funds of Shanghai University of Finance and Economics[CXJJ-2013-449] ; Shanghai Young Teacher Training Scheme of Universities[ZZSWM15019] ; Shanghai Summit and Plateau Discipline ; Scientific and Technological projects of Shenyang[F14-231-1-39] ; National Natural Science Foundation of China (NSFC)[11401194] ; National Natural Science Foundation of China (NSFC)[71271128] ; Fundamental Research Funds for the Central Universities[531107050739] ; State Key Program of National Natural Science Foundation of China[71331006] ; State Key Program of National Natural Science Foundation of China[91546202] ; National Center for Mathematics and Interdisciplinary Sciences (NCMIS) ; Key Laboratory of RCSDS ; Academy of Mathematics and Systems Science (AMSS) ; Chinese Academy of Sciences (CAS)[2008DP173182] ; Shanghai First-class Discipline A, Program for Changjiang Scholars (PCSIRT) ; Innovative Research Team in Shanghai University of Finance and Economics (SUFE)[IRT13077]
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000381578700002
PublisherTAYLOR & FRANCIS INC
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/23542
Collection应用数学研究所
Corresponding AuthorZhang, Feipeng
Affiliation1.Shanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai, Peoples R China
2.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China
3.Hunan Univ, Sch Finance & Stat, 109 Shijiachong Rd, Changsha 410006, Hunan, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Fan, Caiyun,Zhang, Feipeng,Zhou, Yong. Power-transformed linear regression on quantile residual life for censored competing risks data[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS,2016,45(20):5884-5905.
APA Fan, Caiyun,Zhang, Feipeng,&Zhou, Yong.(2016).Power-transformed linear regression on quantile residual life for censored competing risks data.COMMUNICATIONS IN STATISTICS-THEORY AND METHODS,45(20),5884-5905.
MLA Fan, Caiyun,et al."Power-transformed linear regression on quantile residual life for censored competing risks data".COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 45.20(2016):5884-5905.
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