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Nonparametric predictive pairwise comparison with competing risks

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  • Coolen-Maturi, Tahani

Abstract

In reliability, failure data often correspond to competing risks, where several failure modes can cause a unit to fail. This paper presents nonparametric predictive inference (NPI) for pairwise comparison with competing risks data, assuming that the failure modes are independent. These failure modes could be the same or different among the two groups, and these can be both observed and unobserved failure modes. NPI is a statistical approach based on few assumptions, with inferences strongly based on data and with uncertainty quantified via lower and upper probabilities. The focus is on the lower and upper probabilities for the event that the lifetime of a future unit from one group, say Y, is greater than the lifetime of a future unit from the second group, say X. The paper also shows how the two groups can be compared based on particular failure mode(s), and the comparison of the two groups when some of the competing risks are combined is discussed.

Suggested Citation

  • Coolen-Maturi, Tahani, 2014. "Nonparametric predictive pairwise comparison with competing risks," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 146-153.
    • Handle: RePEc:eee:reensy:v:132:y:2014:i:c:p:146-153
    DOI: 10.1016/j.ress.2014.07.014
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    References listed on IDEAS

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    1. T A Maturi & P Coolen-Schrijner & F P A Coolen, 2010. "Nonparametric predictive inference for competing risks," Journal of Risk and Reliability, , vol. 224(1), pages 11-26, March.
    2. Janurová, Kateřina & Briš, Radim, 2014. "A nonparametric approach to medical survival data: Uncertainty in the context of risk in mortality analysis," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 145-152.
    3. Paul H. Kvam & Harshinder Singh, 2001. "On Non‐parametric Estimation of the Survival Function with Competing Risks," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(4), pages 715-724, December.
    4. Coolen-Maturi, Tahani & Coolen, Frank P.A., 2014. "Nonparametric predictive inference for combined competing risks data," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 87-97.
    5. Sarhan, Ammar M. & Hamilton, David C. & Smith, B., 2010. "Statistical analysis of competing risks models," Reliability Engineering and System Safety, Elsevier, vol. 95(9), pages 953-962.
    6. T Coolen-Maturi & F P A Coolen, 2011. "Unobserved, re-defined, unknown or removed failure modes in competing risks," Journal of Risk and Reliability, , vol. 225(4), pages 461-474, December.
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    Cited by:

    1. Fang, Chen & Cui, Lirong, 2021. "Balanced Systems by Considering Multi-state Competing Risks Under Degradation Processes," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    2. Luo, Wei & Zhang, Chun-hua & Chen, Xun & Tan, Yuan-yuan, 2015. "Accelerated reliability demonstration under competing failure modes," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 75-84.
    3. Cui, Lirong & Wu, Bei, 2019. "Extended Phase-type models for multistate competing risk systems," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 1-16.
    4. Coolen-Maturi, Tahani & Coolen, Frank P.A., 2014. "Nonparametric predictive inference for combined competing risks data," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 87-97.

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