Power-transformed linear quantile regression estimation for censored competing risks data

CSpace > 应用数学研究所

	Power-transformed linear quantile regression estimation for censored competing risks data
	Fan, Caiyun 1; Zhang, Feipeng 2; Zhou, Yong3,4
	2017
发表期刊	Statistics and Its Interface
ISSN	1938-7989
卷号	10 期号:2 页码:239-254
摘要	This paper considers a power-transformed linear quantile regression model for censored competing risks data, based on conditional quantiles defined by using the cumulative incidence function. We propose a two-stage estimating procedure for the regression coefficients and the transformation parameter. In the first step, for a given transformation parameter, we develop an unbiased monotone estimating equation for regression parameters in the quantile model, which can be solved by minimizing a L-1 type convex objective function. In the second step, the transformation parameter can be estimated by constructing the cumulative sum processes. The consistency and asymptotic normality of the regression parameters and transformation parameter are derived. The finite-sample performances of the proposed approach are illustrated by simulation studies and an application to the follicular type lymphoma data set.
关键词	Box-Cox transformation Censored data Competing risks Quantile regression
语种	英语
资助项目	Shanghai Pujiang Program[16PJC041] ; Shanghai Young Teacher Training Scheme of Universities[ZZSWM15019] ; Shanghai Summit and Plateau Discipline ; 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) and Innovative Research Team in Shanghai University of Finance and Economics (SUFE)[IRT13077]
WOS研究方向	Mathematical & Computational Biology ; Mathematics
WOS类目	Mathematical & Computational Biology ; Mathematics, Interdisciplinary Applications
WOS记录号	WOS:000389015500008
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/24303
专题	应用数学研究所
通讯作者	Zhang, Feipeng
作者单位	1.Shanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R China 2.Hunan Univ, Sch Finance & Stat, Changsha 410082, Hunan, Peoples R China 3.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai 200433, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Fan, Caiyun,Zhang, Feipeng,Zhou, Yong. Power-transformed linear quantile regression estimation for censored competing risks data[J]. Statistics and Its Interface,2017,10(2):239-254.
APA	Fan, Caiyun,Zhang, Feipeng,&Zhou, Yong.(2017).Power-transformed linear quantile regression estimation for censored competing risks data.Statistics and Its Interface,10(2),239-254.
MLA	Fan, Caiyun,et al."Power-transformed linear quantile regression estimation for censored competing risks data".Statistics and Its Interface 10.2(2017):239-254.