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

Authors:
Edson Z. Martinez;Jorge A. Achcar;Alexandre A. A. Jácome;José S. Santos
Affiliations:
-;-;-;-
Venue:
Computer Methods and Programs in Biomedicine
Year:
2013

Citing 2
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Limited failure population life tests: application to integrated circuit reliablity

Technometrics
A generalized modified Weibull distribution for lifetime modeling

Computational Statistics & Data Analysis

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Abstract

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.