Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Regression models generated by gamma random variables with long-term survivors

  • Ortega, Edwin M.M. (Departamento de Ciencias Exatas, USP) ;
  • Cordeiro, Gauss M. (Departamento de Estatistica, UFPE) ;
  • Hashimoto, Elizabeth M. (Departamento Academico de Matematicas, UTFPR) ;
  • Suzuki, Adriano K. (Departamento de Matematica Aplicada e Estatistica, USP)
  • Received : 2016.09.30
  • Accepted : 2016.11.08
  • Published : 2017.01.31
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Abstract

We propose a flexible cure rate survival model by assuming that the number of competing causes of the event of interest has the Poisson distribution and the time for the event follows the gamma-G family of distributions. The extended family of gamma-G failure-time models with long-term survivors is flexible enough to include many commonly used failure-time distributions as special cases. We consider a frequentist analysis for parameter estimation and derive appropriate matrices to assess local influence on the parameters. Further, various simulations are performed for different parameter settings, sample sizes and censoring percentages. We illustrate the performance of the proposed regression model by means of a data set from the medical area (gastric cancer).

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