Literature DB >> 4089352

An application of Bayesian analysis to medical follow-up data.

J A Achcar, R Brookmeyer, W G Hunter.   

Abstract

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.

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Year:  1985        PMID: 4089352     DOI: 10.1002/sim.4780040411

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  1 in total

1.  A Bayesian approach to Weibull survival models--application to a cancer clinical trial.

Authors:  K Abrams; D Ashby; D Errington
Journal:  Lifetime Data Anal       Date:  1996       Impact factor: 1.588

  1 in total

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