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Bayesian analysis of generalized odds-rate hazards models for survival data

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Abstract

In the analysis of censored survival data Cox proportional hazards model (1972) is extremely popular among the practitioners. However, in many real-life situations the proportionality of the hazard ratios does not seem to be an appropriate assumption. To overcome such a problem, we consider a class of nonproportional hazards models known as generalized odds-rate class of regression models. The class is general enough to include several commonly used models, such as proportional hazards model, proportional odds model, and accelerated life time model. The theoretical and computational properties of these models have been re-examined. The propriety of the posterior has been established under some mild conditions. A simulation study is conducted and a detailed analysis of the data from a prostate cancer study is presented to further illustrate the proposed methodology.

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Authors and Affiliations

  1. Department of Statistics, Calcutta University, Calcutta, 700019, India

    Tathagata Banerjee

  2. Department of Statistics, University of Connecticut, Storrs, CT, 06269, USA

    Ming-Hui Chen, Dipak K. Dey & Sungduk Kim

Authors
  1. Tathagata Banerjee
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  2. Ming-Hui Chen
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  3. Dipak K. Dey
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  4. Sungduk Kim
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Correspondence to Ming-Hui Chen.

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Banerjee, T., Chen, MH., Dey, D.K. et al. Bayesian analysis of generalized odds-rate hazards models for survival data. Lifetime Data Anal 13, 241–260 (2007). https://doi.org/10.1007/s10985-007-9035-3

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  • DOI: https://doi.org/10.1007/s10985-007-9035-3

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