title: Bayesian monitoring of event rates with censored data.
abstract: A Bayesian approach to monitoring event rates with censored data is proposed. A Dirichlet prior for discrete time event probabilities is blended with discrete survival times to provide a posterior distribution that is a mixture of Dirichlets. Approximation of the posterior distribution via data augmentation is discussed. Practical issues involved in implementing the procedure are discussed and illustrated with a simulation of the single arm Cord Blood Transplantation Study where 6-month survival is monitored.
authors.affiliation: Office of Biostatistics Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20892-7938, USA. follmann@helix.nih.gov
authors.forename: D A
authors.initials: DA
authors.lastname: Follmann
authors.forename: P S
authors.initials: PS
authors.lastname: Albert
mesh_terms: D001499:Bayes Theorem; D001699:Biometry; D001855:Bone Marrow Diseases / Q000401:mortality / Q000628:therapy; D003627:Data Interpretation, Statistical; D005312:Fetal Blood; D018380:Hematopoietic Stem Cell Transplantation; D006801:Humans; D016019:Survival Analysis; D013997:Time Factors