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Hazards regression for length-biased and right-censored data

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  • Shen, Pao-sheng

Abstract

When survival data are collected on a cohort of prevalent cases with constant incidence, it is well known that the survival function corresponding to these data is length-biased. For length-biased data, [Wang, M.-C., 1996. Hazard regression analysis with length-biased data. Biometrika 83, 343-354] developed semiparametric estimation procedures for the proportional hazards model. In this article, for length-biased and right-censored data, we construct semiparametric estimation procedures for the proportional and additive hazards models. Simulation results show that semiparametric estimators can outperform nonparametric estimators when censoring is not heavy and truncation is severe.

Suggested Citation

  • Shen, Pao-sheng, 2009. "Hazards regression for length-biased and right-censored data," Statistics & Probability Letters, Elsevier, vol. 79(4), pages 457-465, February.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:4:p:457-465
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    References listed on IDEAS

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    1. Micha Mandel & Rebecca A. Betensky, 2007. "Testing Goodness of Fit of a Uniform Truncation Model," Biometrics, The International Biometric Society, vol. 63(2), pages 405-412, June.
    2. Asgharian M. & MLan C.E. & Wolfson D. B., 2002. "Length-Biased Sampling With Right Censoring: An Unconditional Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 201-209, March.
    3. D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
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    Cited by:

    1. Yu Shen & Jing Ning & Jing Qin, 2017. "Nonparametric and semiparametric regression estimation for length-biased survival data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 3-24, January.
    2. Ahmadi, Jafar & Doostparast, Mahdi & Parsian, Ahmad, 2012. "Estimation with left-truncated and right censored data: A comparison study," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1391-1400.
    3. Micha Mandel & Jacobo de Uña†à lvarez & David K. Simon & Rebecca A. Betensky, 2018. "Inverse probability weighted Cox regression for doubly truncated data," Biometrics, The International Biometric Society, vol. 74(2), pages 481-487, June.
    4. Jacobo Uña-Álvarez, 2013. "Comments on: An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 414-418, September.
    5. Shen, Pao-sheng, 2009. "Semiparametric analysis of survival data with left truncation and right censoring," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4417-4432, October.
    6. Jung-Yu Cheng & Shinn-Jia Tzeng, 2014. "Quantile regression of right-censored length-biased data using the Buckley–James-type method," Computational Statistics, Springer, vol. 29(6), pages 1571-1592, December.

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