Statistics and Its Interface

Volume 12 (2019)

Number 1

Nonparametric estimate of conditional quantile residual lifetime for right censored data

Pages: 61 – 70

DOI: https://dx.doi.org/10.4310/SII.2019.v12.n1.a6

Authors

Yutao Liu (School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, China)

Cunjie Lin (Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China)

Yong Zhou (Institute of Statistics and Interdisciplinary Sciences, Faculty of Economics and Management, East China Normal University, Shanghai, China; and Academy of Mathematics and System Sciences, C.A.S., Beijing, China)

Abstract

A nonparametric approach is proposed to estimate the quantile residual lifetime at a given time while considering the effect of covariates. An estimating equation is constructed and a local Kaplan–Meier estimator is employed to incorporate the covariates in the equation while leaving the distribution of survival time unspecified. Asymptotic properties including both consistency and asymptotic normality of the proposed estimator are established and a resampling method is proposed to estimate the asymptotic variance. Simulation studies are conducted to assess the finite-sample performance of the estimator, and an HIV survival data is analyzed using the proposed method.

Keywords

local Kaplan–Meier estimate,quantile residual lifetime, right censored data

Full Text (PDF format)

Liu’s work was supported by National Natural Science Foundation of China (11401603), the Fundamental Research Funds for the Central Universities(QL 18009) and Discipline Foundation of Central University of Finance and Economics (CUFESAM201811). Lin’s work was supported by National Natural Science Foundation of China (11701561), the MOE Project of Key Research Institute of Humanities and Social Sciences at Universities (16JJD910002) and fund for building world-class universities (disciplines) of Renmin University of China. Zhou’s work was supported by the State Key Program of National Natural Science Foundation of China (71331006), the State Key Program in the Major Research Plan of National Natural Science Foundation of China (91546202).

Received 4 April 2017

Published 26 October 2018