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Composite Estimating Equation Method for the Accelerated Failure Time Model with Length-biased Sampling Data
Qiu, Zhiping1,2; Qin, Jing3; Zhou, Yong4
2016-06-01
Source PublicationSCANDINAVIAN JOURNAL OF STATISTICS
ISSN0303-6898
Volume43Issue:2Pages:396-415
AbstractLength-biased sampling data are often encountered in the studies of economics, industrial reliability, epidemiology, genetics and cancer screening. The complication of this type of data is due to the fact that the observed lifetimes suffer from left truncation and right censoring, where the left truncation variable has a uniform distribution. In the Cox proportional hazards model, Huang & Qin (Journal of the American Statistical Association, 107, 2012, p. 107) proposed a composite partial likelihood method which not only has the simplicity of the popular partial likelihood estimator, but also can be easily performed by the standard statistical software. The accelerated failure time model has become a useful alternative to the Cox proportional hazards model. In this paper, by using the composite partial likelihood technique, we study this model with length-biased sampling data. The proposed method has a very simple form and is robust when the assumption that the censoring time is independent of the covariate is violated. To ease the difficulty of calculations when solving the non-smooth estimating equation, we use a kernel smoothed estimation method (Heller; Journal of the American Statistical Association, 102, 2007, p. 552). Large sample results and a re-sampling method for the variance estimation are discussed. Some simulation studies are conducted to compare the performance of the proposed method with other existing methods. A real data set is used for illustration.
Keywordaccelerated failure time model composite estimating equation kernel smoothing length-biased sampling data rank estimator
DOI10.1111/sjos.12182
Language英语
Funding ProjectNational Natural Science Foundation of China (NSFC)[71271128] ; National Natural Science Foundation of China[71331006] ; NCMIS, Key Laboratory of RCSDS, AMSS, CAS[2008DP173182] ; Shanghai First-class Discipline A ; IRTSHUFE, PCSIRT[IRT13077] ; Natural Science Foundation of Fujian Province, China[2015J01583]
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000382553500011
PublisherWILEY-BLACKWELL
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/23499
Collection应用数学研究所
Corresponding AuthorZhou, Yong
Affiliation1.Huaqiao Univ, Sch Math Sci, Quanzhou, Peoples R China
2.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China
3.NIAID, Biostat Res Branch, Bethesda, MD USA
4.Chinese Acad Sci, Inst Appl Math, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Qiu, Zhiping,Qin, Jing,Zhou, Yong. Composite Estimating Equation Method for the Accelerated Failure Time Model with Length-biased Sampling Data[J]. SCANDINAVIAN JOURNAL OF STATISTICS,2016,43(2):396-415.
APA Qiu, Zhiping,Qin, Jing,&Zhou, Yong.(2016).Composite Estimating Equation Method for the Accelerated Failure Time Model with Length-biased Sampling Data.SCANDINAVIAN JOURNAL OF STATISTICS,43(2),396-415.
MLA Qiu, Zhiping,et al."Composite Estimating Equation Method for the Accelerated Failure Time Model with Length-biased Sampling Data".SCANDINAVIAN JOURNAL OF STATISTICS 43.2(2016):396-415.
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