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Destructive weighted Poisson cure rate models with bivariate random effects: Classical and Bayesian approaches

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  • Gallardo, Diego I.
  • Bolfarine, Heleno
  • Pedroso-de-Lima, Antonio Carlos

Abstract

In this paper, random effects are included in the destructive weighted Poisson cure rate model. For parameter estimation we implemented a classical approach based on the restricted maximum likelihood (REML) methodology and a Bayesian approach based on Dirichlet process priors. A small scale simulation study is conducted to discuss parameter recovery and the performance of the proposed methodology is illustrated with a real data example.

Suggested Citation

  • Gallardo, Diego I. & Bolfarine, Heleno & Pedroso-de-Lima, Antonio Carlos, 2016. "Destructive weighted Poisson cure rate models with bivariate random effects: Classical and Bayesian approaches," Computational Statistics & Data Analysis, Elsevier, vol. 98(C), pages 31-45.
    • Handle: RePEc:eee:csdana:v:98:y:2016:i:c:p:31-45
    DOI: 10.1016/j.csda.2015.12.006
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    References listed on IDEAS

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    1. Li, Chin-Shang & Taylor, Jeremy M. G. & Sy, Judy P., 2001. "Identifiability of cure models," Statistics & Probability Letters, Elsevier, vol. 54(4), pages 389-395, October.
    2. Carvalho Lopes, Celia Mendes & Bolfarine, Heleno, 2012. "Random effects in promotion time cure rate models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 75-87, January.
    3. M. C. Donohue & R. Overholser & R. Xu & F. Vaida, 2011. "Conditional Akaike information under generalized linear and proportional hazards mixed models," Biometrika, Biometrika Trust, vol. 98(3), pages 685-700.
    4. Jara, Alejandro & Quintana, Fernando & San Marti­n, Ernesto, 2008. "Linear mixed models with skew-elliptical distributions: A Bayesian approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 5033-5045, July.
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