Dados de sobrevivência multivariados na presença de covariáveis e observações censuradas: uma abordagem bayesiana

AUTOR(ES)
DATA DE PUBLICAÇÃO

2010

RESUMO

In this work, we introduce a Bayesian Analysis for survival multivariate data in the presence of a covariate vector and censored observations. Different frailtiesor latent variables are considered to capture the correlation among the survival times for the same individual. We also introduce a Bayesian analysis for some of the most popular bivariate exponential distributions introduced in the literature. A Bayesian analysis is also introduced for the Block &Basu bivariate exponential distribution using Markov Chain Monte Carlo (MCMC) methods and considering lifetimes in presence of covariates and censored data. In another topic, we introduce a Bayesian Analysis for bivariate lifetime data in the presence of covariates and censoring data assuming different bivariate Weibull distributions derived from some existing copula functions. A great computational simplification to simulate samples for the joint posterior distribution is obtained using the WinBUGS software. Numerical illustrations are introduced considering real data sets considering every proposed methodology.

ASSUNTO(S)

block &basu bivariate exponential distribution copula functions mcmc methods censoring data algorítmos mcmc estatistica inferência bayesiana análise de sobrevivência Álise bayesiana distribuição exponencial bivariada de block &basu distribuições bivariadas weibull covariáveis cópula covariates bayesian analysis dados censurados bivariate weibull distributions

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