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Block and Basu bivariate lifetime distribution in the presence of cure fraction

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  • Jorge Alberto Achcar
  • Em�lio Augusto Coelho-Barros
  • Josmar Mazucheli

Abstract

This paper presents estimates for the parameters included in the Block and Basu bivariate lifetime distributions in the presence of covariates and cure fraction, applied to analyze survival data when some individuals may never experience the event of interest and two lifetimes are associated with each unit. A Bayesian procedure is used to get point and confidence intervals for the unknown parameters. Posterior summaries of interest are obtained using standard Markov Chain Monte Carlo methods in rjags package for R software. An illustration of the proposed methodology is given for a Diabetic Retinopathy Study data set.

Suggested Citation

  • Jorge Alberto Achcar & Em�lio Augusto Coelho-Barros & Josmar Mazucheli, 2013. "Block and Basu bivariate lifetime distribution in the presence of cure fraction," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1864-1874, September.
    • Handle: RePEc:taf:japsta:v:40:y:2013:i:9:p:1864-1874
    DOI: 10.1080/02664763.2013.798630
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    References listed on IDEAS

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    1. Carlos dos Santos & Jorge Alberto Achcar, 2011. "A Bayesian analysis for the Block and Basu bivariate exponential distribution in the presence of covariates and censored data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2213-2223.
    2. Nandini Kannan & Debasis Kundu & P. Nair & R. C. Tripathi, 2010. "The generalized exponential cure rate model with covariates," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(10), pages 1625-1636.
    3. Jorge Achcar & Roseli Leandro, 1998. "Use of Markov Chain Monte Carlo Methods in a Bayesian Analysis of the Block and Basu Bivariate Exponential Distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 50(3), pages 403-416, September.
    4. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    5. Vicente Cancho & Heleno Bolfarine, 2001. "Modeling the presence of immunes by using the exponentiated-Weibull model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(6), pages 659-671.
    6. Berg, Andreas & Meyer, Renate & Yu, Jun, 2004. "Deviance Information Criterion for Comparing Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 107-120, January.
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    Cited by:

    1. S. Mirhosseini & M. Amini & D. Kundu & A. Dolati, 2015. "On a new absolutely continuous bivariate generalized exponential distribution," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 61-83, March.

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