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An improper form of Weibull distribution for competing risks analysis with Bayesian approach

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  • A. R. Baghestani
  • F. S. Hosseini-Baharanchi

Abstract

In survival analysis, individuals may fail due to multiple causes of failure called competing risks setting. Parametric models such as Weibull model are not improper that ignore the assumption of multiple failure times. In this study, a novel extension of Weibull distribution is proposed which is improper and then can incorporate to the competing risks framework. This model includes the original Weibull model before a pre-specified time point and an exponential form for the tail of the time axis. A Bayesian approach is used for parameter estimation. A simulation study is performed to evaluate the proposed model. The conducted simulation study showed identifiability and appropriate convergence of the proposed model. The proposed model and the 3-parameter Gompertz model, another improper parametric distribution, are fitted to the acute lymphoblastic leukemia dataset.

Suggested Citation

  • A. R. Baghestani & F. S. Hosseini-Baharanchi, 2019. "An improper form of Weibull distribution for competing risks analysis with Bayesian approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 46(13), pages 2409-2417, October.
    • Handle: RePEc:taf:japsta:v:46:y:2019:i:13:p:2409-2417
    DOI: 10.1080/02664763.2019.1597027
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    Cited by:

    1. Muqrin A. Almuqrin & Mukhtar M. Salah & Essam A. Ahmed, 2022. "Statistical Inference for Competing Risks Model with Adaptive Progressively Type-II Censored Gompertz Life Data Using Industrial and Medical Applications," Mathematics, MDPI, vol. 10(22), pages 1-38, November.

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