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Inference on quantile residual life function under right-censored data

Author

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  • Cunjie Lin
  • Li Zhang
  • Yong Zhou

Abstract

The quantile residual lifetime function is a comprehensive quantitative description of a residual lifetime. Under the assumption of independent censoring, a naive estimator for the quantile residual lifetime function can be obtained by inverting the Kaplan--Meier estimator. However, this naive estimator is biased when survival and censoring times are dependent. In this paper, we propose a method for estimating the quantile residual lifetime function, taking into account the covariates and relaxing the assumption of independent censoring. To compare two quantile residual lifetime functions at fixed time points, we construct two test statistics which are easy to implement. We also derive the asymptotic properties for the proposed estimator and test statistics. A re-sampling method for estimating the asymptotic variance of the proposed estimator is provided. Simulation studies are conducted to assess the finite sample properties of the estimator and the performance of the test statistics. We also apply the proposed method to the real data and report some interesting results.

Suggested Citation

  • Cunjie Lin & Li Zhang & Yong Zhou, 2016. "Inference on quantile residual life function under right-censored data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(3), pages 617-643, September.
    • Handle: RePEc:taf:gnstxx:v:28:y:2016:i:3:p:617-643
    DOI: 10.1080/10485252.2016.1190841
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