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

• Autor(a) principal: Santos, Carlos Aparecido dos
• Data de Publicação: 2010
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFSCAR
• Texto Completo: https://repositorio.ufscar.br/handle/ufscar/4483
• topic: Análise de sobrevivência; Inferência bayesiana; Cópula; Algorítmos MCMC; Dados censurados; Distribuições bivariadas Weibull; Distribuição exponencial bivariada de Block & Basu; Álise Bayesiana; Covariáveis; Bivariate Weibull distributions; Block & Basu bivariate exponential distribution; Copula functions; MCMC methods; Bayesian analysis; Censoring data; Covariates; CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA::ESTATISTICA

In this work, we introduce a Bayesian Analysis for survival multivariate data in the presence of a covariate vector and censored observations. Different frailties or 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.