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A series of two-sample non-parametric tests for quantile residual life time

Author

Listed:
  • Yimeng Liu

    (University of Pittsburgh)

  • Liwen Wu

    (University of Pittsburgh)

  • Gong Tang

    (University of Pittsburgh)

  • Abdus S. Wahed

    (University of Pittsburgh)

Abstract

Quantile residual lifetime (QRL) is of significant interest in many clinical studies as an easily interpretable quantity compared to other summary measures of survival distributions. In cancer or other chronic diseases, treatments are often compared based on the distributions or quantiles of the residual lifetime. Thus a common problem of interest is to test the equality of the QRL between two populations. In this paper, we propose two classes of tests to compare two QRLs; one class is based on the difference between two estimated QRLs, and the other is based on the estimating function of the QRL, where the estimated QRL from one sample is plugged into the QRL-estimating-function of the other sample. We outline the asymptotic properties of these test statistics. Simulation studies demonstrate that the proposed tests produced Type I errors closer to the nominal level and are superior to some existing tests based on both Type I error and power. Our proposed test statistics are also computationally less intensive and more straightforward compared to tests based on the confidence intervals. We applied the proposed methods to a randomized multicenter phase III trial for breast cancer patients.

Suggested Citation

  • Yimeng Liu & Liwen Wu & Gong Tang & Abdus S. Wahed, 2023. "A series of two-sample non-parametric tests for quantile residual life time," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 234-252, January.
    • Handle: RePEc:spr:lifeda:v:29:y:2023:i:1:d:10.1007_s10985-022-09580-6
    DOI: 10.1007/s10985-022-09580-6
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    References listed on IDEAS

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    1. Alan E. Gelfand & Athanasios Kottas, 2003. "Bayesian Semiparametric Regression for Median Residual Life," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(4), pages 651-665, December.
    2. Jong-Hyeon Jeong & Sin-Ho Jung & Joseph P. Costantino, 2008. "Nonparametric Inference on Median Residual Life Function," Biometrics, The International Biometric Society, vol. 64(1), pages 157-163, March.
    3. David M. Vock & Anastasios A. Tsiatis & Marie Davidian & Eric B. Laber & Wayne M. Tsuang & C. Ashley Finlen Copeland & Scott M. Palmer, 2013. "Assessing the Causal Effect of Organ Transplantation on the Distribution of Residual Lifetime," Biometrics, The International Biometric Society, vol. 69(4), pages 820-829, December.
    4. Tsung-Hsien Tsai & Wei-Yann Tsai & Yunchan Chi & Sheng-Mao Chang, 2016. "Confidence intervals for the ratio of two median residual lifetimes with left-truncated and right-censored data," Biometrics, The International Biometric Society, vol. 72(1), pages 232-241, March.
    5. David C. Schmittlein & Donald G. Morrison, 1981. "The Median Residual Lifetime: A Characterization Theorem and an Application," Operations Research, INFORMS, vol. 29(2), pages 392-399, April.
    6. Sin-Ho Jung & Jong-Hyeon Jeong & Hanna Bandos, 2009. "Regression on Quantile Residual Life," Biometrics, The International Biometric Society, vol. 65(4), pages 1203-1212, December.
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