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A Bayesian Cure Rate Model Based on the Power Piecewise Exponential Distribution

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Abstract

Cure rate models have been used in a number of fields. These models are applied to analyze survival data when the population has a proportion of subjects insusceptible to the event of interest. In this paper, we propose a new cure rate survival model formulated under a competing risks setup. The number of competing causes follows the negative binomial distribution, while for the latent times we posit the power piecewise exponential distribution. Samples from the posterior distribution are drawn through MCMC methods. Some properties of the estimators are assessed in a simulation study. A dataset on cutaneous melanoma is analyzed using the proposed model as well as some existing models for the sake of comparison.

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Acknowledgements

We would like to thank two reviewers for their comments, which helped us to improve our paper. The work of the first author is partially supported by CNPq, Brazil. Research carried out using the computational resources of the Center for Mathematical Sciences Applied to Industry (CeMEAI) funded by FAPESP, Brazil (grant 2013/07375-0).

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Correspondence to Mário de Castro.

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de Castro, M., Gómez, Y.M. A Bayesian Cure Rate Model Based on the Power Piecewise Exponential Distribution. Methodol Comput Appl Probab 22, 677–692 (2020). https://doi.org/10.1007/s11009-019-09728-2

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