Comput Methods Programs Biomed - Mixture and non-mixture cure fraction models based on the generalized modified Weibull distribution with an application to gastric cancer data.

Tópicos

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Resumo

The cure fraction models are usually used to model lifetime time data with long-term survivors. In the present article, we introduce a Bayesian analysis of the four-parameter generalized modified Weibull (GMW) distribution in presence of cure fraction, censored data and covariates. In order to include the proportion of "cured" patients, mixture and non-mixture formulation models are considered. To demonstrate the ability of using this model in the analysis of real data, we consider an application to data from patients with gastric adenocarcinoma. Inferences are obtained by using MCMC (Markov Chain Monte Carlo) methods.

Resumo Limpo

cure fraction model usual use model lifetim time data longterm survivor present articl introduc bayesian analysi fourparamet general modifi weibul gmw distribut presenc cure fraction censor data covari order includ proport cure patient mixtur nonmixtur formul model consid demonstr abil use model analysi real data consid applic data patient gastric adenocarcinoma infer obtain use mcmc markov chain mont carlo method

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