title: Bayesian analysis and model selection for interval-censored survival data.
abstract: Interval-censored data occur in survival analysis when the survival time of each patient is only known to be within an interval and these censoring intervals differ from patient to patient. For such data, we present some Bayesian discretized semiparametric models, incorporating proportional and nonproportional hazards structures, along with associated statistical analyses and tools for model selection using sampling-based methods. The scope of these methodologies is illustrated through a reanalysis of a breast cancer data set (Finkelstein, 1986, Biometrics 42, 845-854) to test whether the effect of covariate on survival changes over time.
authors.affiliation: Department of Mathematics, University of New Hampshire, Durham 03824-3591, USA. sinha@purabi.unh.edu
authors.forename: D
authors.initials: D
authors.lastname: Sinha
authors.forename: M H
authors.initials: MH
authors.lastname: Chen
authors.forename: S K
authors.initials: SK
authors.lastname: Ghosh
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001699:Biometry; D001943:Breast Neoplasms / Q000401:mortality / Q000628:therapy; D005260:Female; D006801:Humans; D015233:Models, Statistical; D016016:Proportional Hazards Models; D016019:Survival Analysis; D013997:Time Factors