MOTIVATION A common task in microarray data analysis consists of identifying genes associated with a phenotype. When the outcomes of interest are censored time-to-event data, standard approaches assess the effect of genes by fitting univariate survival models. In this paper, we propose a Bayesian variable selection approach, which allows the identification of relevant markers by jointly assessi...

In this paper a Bayesian approach for accelerated life testing will be considered. It will be assumed that the failure times at the different stress levels follow a Weibull distribution and exponential distribution, respectively. In accelerated life tests, the components are exposed to an environment that is more severe that the usual environment, such that the components will fail in a shorter...

Abstract Background Survival analysis is the most appropriate method of for time-to-event data. The classical accelerated failure-time model a more powerful and interpretable than Cox proportional hazards model, provided that imposed distribution homoscedasticity assumptions satisfied. However, real data are heteroscedastic which violates fundamental assumption consequently, statistical inferen...