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Proportional Mean Residual Life Model with Varying Coefficients for length-biased and Right-Censored Data

Acta Mathematica Sinica,English Series 2020年第5期36卷 578-596页

作者： Da XU Yong ZHOU Key Laboratory of Applied Statistics of MOE and School of Mathematics and Statistics Northeast Normal UniversityChangchun 130024P.R.China Key Laboratory of Advanced Theory and Application in Statistics and Data Science MOEAcademy of Statistics and Interdisciplinary SciencesEast China Normal UniversityShanghai 200062P.R.China Academy of Mathematics and Systems Sciences Chinese Academy of SciencesBeijing 100190P.R.China

length-biased data are encountered in many fields,including economics,engineering and epidemiological cohort studies.There are two main challenges in the analysis of such data:the assumption of independent censoring is violated and the assumed model for the underlying population is no longer satisfied for the observed data.In this paper,a proportional mean residual life varyingcoefficient model for length-biased data is considered and a local pseudo likelihood method is proposed for estimating the coefficient functions in the model.Asymptotic properties are investigated for the proposed estimators.The finite sample performance of the proposed methodology is demonstrated by simulation studies.Finally,the method is applied to a real data set concerning the Academy Awards.

关键词： length-biased data proportional hazards model mean residual life varying-coefficient model

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Semiparametric quantile-difference estimation for length-biased and right-censored data

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Science China Mathematics 2019年第9期62卷 1823-1838页

作者： Yutao Liu Shucong Zhang Yong Zhou School of Statistics and Mathematics Central University of Finance and EconomicsBeijing100081China School of Statistics and Management Shanghai University of Finance and EconomicsShanghai200433China Key Laboratory of Advanced Theory and Application in Statistics and Data Science(MOE) Institute of Statistics and Interdisciplinary Sciences and School of StatisticsEast China Normal UniversityShanghai200241China

Prevalent cohort studies frequently involve length-biased and right-censored data, a fact that has drawn considerable attention in survival analysis. In this article, we consider survival data arising from lengthbiased sampling, and propose a new semiparametric-model-based approach to estimate quantile differences of failure time. We establish the asymptotic properties of our new estimators theoretically under mild technical conditions, and propose a resampling method for estimating their asymptotic variance. We then conduct simulations to evaluate the empirical performance and efficiency of the proposed estimators, and demonstrate their application by a real data analysis.

关键词： quantile differences length-biased sampling right-censored proportional hazards model

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