title: Bayesian inference of the Weibull model based on interval-censored survival data.
abstract: Interval-censored data consist of adjacent inspection times that surround an unknown failure time. We have in this paper reviewed the classical approach which is maximum likelihood in estimating the Weibull parameters with interval-censored data. We have also considered the Bayesian approach in estimating the Weibull parameters with interval-censored data under three loss functions. This study became necessary because of the limited discussion in the literature, if at all, with regard to estimating the Weibull parameters with interval-censored data using Bayesian. A simulation study is carried out to compare the performances of the methods. A real data application is also illustrated. It has been observed from the study that the Bayesian estimator is preferred to the classical maximum likelihood estimator for both the scale and shape parameters.
authors.affiliation: Institute for Mathematical Research, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia. chris@chrisguure.com
authors.forename: Chris Bambey
authors.initials: CB
authors.lastname: Guure
authors.forename: Noor Akma
authors.initials: NA
authors.lastname: Ibrahim
authors.forename: Mohd Bakri
authors.initials: MB
authors.lastname: Adam
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000188:drug therapy / Q000401:mortality* / Q000532:radiotherapy; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D011336:Probability; D012189:Retrospective Studies; D016019:Survival Analysis