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TitleNonparametric and semiparametric estimation of quantile residual lifetime for length-biased and right-censored data
Creator
Date Issued2017-06
Source PublicationCanadian Journal of Statistics
ISSN0319-5724
Volume45Issue:2Pages:220-250
Abstract

Quantile residual lifetime models are often of concern in survival analysis, especially when studying a chronic or irreversible disease like dementia. In the past several decades residual life models have been studied extensively with right-censored survival data. However these methods are not suitable to analyze the length-biased and right-censored data from the prevalent cohort sampling. In this article we propose nonparametric and semiparametric model-based procedures to estimate the quantile residual lifetime with censored length-biased data. Two test statistics are established for comparing the quantile residual lifetimes of two groups, evaluated, respectively, on ratio and difference in terms of type I error probabilities and powers. Some simulations are conducted to compare the proposed method with existing approaches. Real dementia data from the National Alzheimer's Coordinating Center are used to illustrate the proposed estimation methods by estimating the quantile residual lifetimes of the dementia patients. The Canadian Journal of Statistics 45: 220–250; 2017 © 2017 Statistical Society of Canada.

KeywordCox model length-bias MSC 2010: Primary 62N01 quantile residual lifetime model right-censoring secondary 62N02
DOI10.1002/cjs.11319
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000400027400006
Scopus ID2-s2.0-85018263975
Citation statistics
Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/6359
CollectionFaculty of Science and Technology
Corresponding AuthorZhou, Yong
Affiliation
1.Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing,100190,China
2.School of Statistics and Management,Shanghai University of Finance and Economics,Shanghai,200433,China
3.Beijing Normal University-Hong Kong Baptist University,United International College,Zhuhai,519085,China
4.Department of Biostatistics,University of Washington,Seattle,98195,United States
5.Biostatistics Unit,U.S. Department of Veterans Affairs Seattle Medical Center,Seattle,98104,United States
Recommended Citation
GB/T 7714
Wang, Yixin,Zhou, Sherry Zhefang,Zhou, Xiaohuaet al. Nonparametric and semiparametric estimation of quantile residual lifetime for length-biased and right-censored data[J]. Canadian Journal of Statistics, 2017, 45(2): 220-250.
APA Wang, Yixin, Zhou, Sherry Zhefang, Zhou, Xiaohua, & Zhou, Yong. (2017). Nonparametric and semiparametric estimation of quantile residual lifetime for length-biased and right-censored data. Canadian Journal of Statistics, 45(2), 220-250.
MLA Wang, Yixin,et al."Nonparametric and semiparametric estimation of quantile residual lifetime for length-biased and right-censored data". Canadian Journal of Statistics 45.2(2017): 220-250.
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