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A flexible model for survival data with a cure rate: a Bayesian approach

Author

Listed:
  • Vicente Cancho
  • Josemar Rodrigues
  • Mario de Castro

Abstract

In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real data set.

Suggested Citation

  • Vicente Cancho & Josemar Rodrigues & Mario de Castro, 2011. "A flexible model for survival data with a cure rate: a Bayesian approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(1), pages 57-70.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:1:p:57-70
    DOI: 10.1080/02664760903254052
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    Citations

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    Cited by:

    1. Amanda D’Andrea & Ricardo Rocha & Vera Tomazella & Francisco Louzada, 2018. "Negative Binomial Kumaraswamy-G Cure Rate Regression Model," JRFM, MDPI, vol. 11(1), pages 1-14, January.
    2. Francisco Louzada & M�rio de Castro & Vera Tomazella & Jhon F.B. Gonzales, 2014. "Modeling categorical covariates for lifetime data in the presence of cure fraction by Bayesian partition structures," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(3), pages 622-634, March.
    3. Vicente G. Cancho & Gladys D. C. Barriga & Gauss M. Cordeiro & Edwin M. M. Ortega & Adriano K. Suzuki, 2021. "Bayesian survival model induced by frailty for lifetime with long‐term survivors," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(3), pages 299-323, August.
    4. Mário Castro & Yolanda M. Gómez, 2020. "A Bayesian Cure Rate Model Based on the Power Piecewise Exponential Distribution," Methodology and Computing in Applied Probability, Springer, vol. 22(2), pages 677-692, June.
    5. Reza Azimi & Mahdy Esmailian & Diego I. Gallardo & Héctor J. Gómez, 2022. "A New Cure Rate Model Based on Flory–Schulz Distribution: Application to the Cancer Data," Mathematics, MDPI, vol. 10(24), pages 1-17, December.
    6. Vicente G. Cancho & Elizbeth C. Bedia & Gauss M. Cordeiro & Fábio Prataviera & Edwin M. M. Ortega & Ana P. J. E. Santo, 2023. "A survival regression with cure fraction applied to cervical cancer," Computational Statistics, Springer, vol. 38(1), pages 403-418, March.

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