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Linear life expectancy regression with censored data

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  • Y. Q. Chen
  • S. Cheng

Abstract

In the statistical literature, life expectancy is usually characterised by the mean residual life function. Regression models are thus needed to study the association between the mean residual life functions and their covariates. In this paper, we consider a linear mean residual life model and develop inference procedures in the presence of potential censoring. The new model and inference procedures are applied to the Stanford heart transplant data. Semiparametric efficiency calculations and information bounds are also considered. Copyright 2006, Oxford University Press.

Suggested Citation

  • Y. Q. Chen & S. Cheng, 2006. "Linear life expectancy regression with censored data," Biometrika, Biometrika Trust, vol. 93(2), pages 303-313, June.
    • Handle: RePEc:oup:biomet:v:93:y:2006:i:2:p:303-313
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    File URL: http://hdl.handle.net/10.1093/biomet/93.2.303
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    Cited by:

    1. Peng Jin & Anne Zeleniuch-Jacquotte & Mengling Liu, 2020. "Generalized mean residual life models for case-cohort and nested case-control studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 789-819, October.
    2. Zahra Mansourvar & Torben Martinussen & Thomas H. Scheike, 2016. "An Additive–Multiplicative Restricted Mean Residual Life Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 487-504, June.
    3. Yixin Wang & Ying Qing Chen, 2019. "Estimating Attributable Life Expectancy Under the Proportional Mean Residual Life Model," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 659-676, December.
    4. Kyu Hyun Kim & Daniel J. Caplan & Sangwook Kang, 2023. "Smoothed quantile regression for censored residual life," Computational Statistics, Springer, vol. 38(2), pages 1001-1022, June.
    5. Wu, Hongping & Cao, Xiaomin & Du, Caifeng, 2019. "Estimating equations of additive mean residual life model with censored length-biased data," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.
    6. V. N. Sreeja & P. G. Sankaran, 2007. "Proportional mean residual life model for gap time distributions of recurrent events," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 319-336.
    7. Zahra Mansourvar & Torben Martinussen & Thomas H. Scheike, 2015. "Semiparametric regression for restricted mean residual life under right censoring," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(12), pages 2597-2613, December.
    8. Ruiwen Zhou & Jianguo Sun, 2022. "Estimation of the Proportional Mean Residual Life Model with Internal and Longitudinal Covariates," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(3), pages 550-563, December.
    9. Yang, Guangren & Zhou, Yong, 2014. "Semiparametric varying-coefficient study of mean residual life models," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 226-238.

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