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Estimation of the survival function with redistribution algorithm under semi-competing risks data

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  • Hsieh, Jin-Jian
  • Hsu, Chia-Hao

Abstract

This paper focuses on the estimation of the survival function of the non-terminal event time for semi-competing risks data. Without extra assumptions, we cannot make inference on the non-terminal event time because the non-terminal event time is dependently censored by the terminal event time. Thus, we utilize the Archimedean copula model to specify the dependency between the non-terminal event time and the terminal event time. Under the Archimedean copula assumption, we apply the redistribution method to estimate the survival function of the non-terminal event time and compare it with the copula-graphic estimator introduced by Lakhal et al. (2008). We also apply our suggested approach to analyze the Bone Marrow Transplant data.

Suggested Citation

  • Hsieh, Jin-Jian & Hsu, Chia-Hao, 2018. "Estimation of the survival function with redistribution algorithm under semi-competing risks data," Statistics & Probability Letters, Elsevier, vol. 132(C), pages 1-6.
    • Handle: RePEc:eee:stapro:v:132:y:2018:i:c:p:1-6
    DOI: 10.1016/j.spl.2017.09.003
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    References listed on IDEAS

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    1. Weijing Wang, 2003. "Estimating the association parameter for copula models under dependent censoring," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 257-273, February.
    2. A. Adam Ding & Guangkai Shi & Weijing Wang & Jin‐Jian Hsieh, 2009. "Marginal Regression Analysis for Semi‐Competing Risks Data Under Dependent Censoring," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 481-500, September.
    3. Jin‐Jian Hsieh & Weijing Wang & A. Adam Ding, 2008. "Regression analysis based on semicompeting risks data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 3-20, February.
    4. Rivest, Louis-Paul & Wells, Martin T., 2001. "A Martingale Approach to the Copula-Graphic Estimator for the Survival Function under Dependent Censoring," Journal of Multivariate Analysis, Elsevier, vol. 79(1), pages 138-155, October.
    5. Hongyu Jiang & Jason P. Fine & Rick Chappell, 2005. "Semiparametric Analysis of Survival Data with Left Truncation and Dependent Right Censoring," Biometrics, The International Biometric Society, vol. 61(2), pages 567-575, June.
    6. Hongyu Jiang & Jason P. Fine & Michael R. Kosorok & Rick Chappell, 2005. "Pseudo Self‐Consistent Estimation of a Copula Model with Informative Censoring," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(1), pages 1-20, March.
    7. Lajmi Lakhal & Louis-Paul Rivest & Belkacem Abdous, 2008. "Estimating Survival and Association in a Semicompeting Risks Model," Biometrics, The International Biometric Society, vol. 64(1), pages 180-188, March.
    8. Limin Peng & Jason P. Fine, 2007. "Regression Modeling of Semicompeting Risks Data," Biometrics, The International Biometric Society, vol. 63(1), pages 96-108, March.
    9. Shu-Hui Chang, 2000. "A Two-Sample Comparison for Multiple Ordered Event Data," Biometrics, The International Biometric Society, vol. 56(1), pages 183-189, March.
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