Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Cure rate proportional odds models with spatial frailties for interval-censored data

  • Yiqi, Bao (Departamento de Matematica Aplicada e Estatistica, Universidade de Sao Paulo) ;
  • Cancho, Vicente Garibay (Departamento de Matematica Aplicada e Estatistica, Universidade de Sao Paulo) ;
  • Louzada, Francisco (Departamento de Matematica Aplicada e Estatistica, Universidade de Sao Paulo) ;
  • Suzuki, Adriano Kamimura (Departamento de Matematica Aplicada e Estatistica, Universidade de Sao Paulo)
  • Received : 2017.07.08
  • Accepted : 2017.11.07
  • Published : 2017.11.30
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Abstract

This paper presents proportional odds cure models to allow spatial correlations by including spatial frailty in the interval censored data setting. Parametric cure rate models with independent and dependent spatial frailties are proposed and compared. Our approach enables different underlying activation mechanisms that lead to the event of interest; in addition, the number of competing causes which may be responsible for the occurrence of the event of interest follows a Geometric distribution. Markov chain Monte Carlo method is used in a Bayesian framework for inferential purposes. For model comparison some Bayesian criteria were used. An influence diagnostic analysis was conducted to detect possible influential or extreme observations that may cause distortions on the results of the analysis. Finally, the proposed models are applied for the analysis of a real data set on smoking cessation. The results of the application show that the parametric cure model with frailties under the first activation scheme has better findings.

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References

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