An application of bayesian analysis to medical follow‐up data

Jorge A. Achcar, Ron Brookmeyer, William G. Hunter

Research output: Contribution to journalArticlepeer-review


Posterior distributions can provide effective summaries of the main conclusions of medical follow‐up studies. In this article, we use Bayesian methods for the analysis of survival data. We describe posterior distributions for various parameters of clinical interest in the presence of arbitrary right censorship. Non‐informative reference priors result from transformation of a two‐parameter Weibull model into a location‐scale family. We suggest an approach for checking adequacy. For illustration, we apply the methods to a well‐known acute leukemia data set.

Original languageEnglish (US)
Pages (from-to)509-520
Number of pages12
JournalStatistics in Medicine
Issue number4
StatePublished - 1985


  • Bayesian analysis
  • Censoring
  • Medical follow‐up study
  • Weibull distribution

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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