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Bayesian Monitoring of Event Rates with Censored Data
Author(s) -
Follmann Dean A.,
Albert Paul S.
Publication year - 1999
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.1999.00603.x
Subject(s) - bayesian probability , posterior probability , event (particle physics) , dirichlet distribution , statistics , computer science , event data , mathematics , econometrics , mathematical analysis , physics , quantum mechanics , covariate , boundary value problem
Summary. 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.