Bayesian analysis and model selection for interval censored survival data

To the best of our knowledge this is the first time that the effect of interval censoring has been investigated in the MPR survival model setting and the first time that MPR models

In this paper, we proposed a new method for analyzing current status data and more gen- erally, interval censored data, using the accelerated failure time model. The new

keywords: Survival analysis, Gompertz distribution, censored data, max- imum likelihood estimation, Bayesian inference, defective

(1998), ‘A nonparametric estimator of survival functions for arbitrarily truncated and censored data’, Lifetime Data Analysis 4 , 187–202.

In the first project, we consider efficient semiparametric estimation of the accelerated failure time (AFT) model with partly interval-censored (PIC) data, which arise when the event

We began the analysis by considering the effect of a single covariate age in the model. To create a hypothetical interval-censored competing risks setting, the data are

We can obtain complete or (left-truncated and) right-censored data after imputation of the (left-truncated and) interval-censored data. Subsequently, standard statistical methods can

(Nassar & Eissa 2005) used the Bayesian approach for type II censored data to estimate the two shape parameters and the reliability function of the Exponentiated Weibull