title: An application of Bayesian analysis to medical follow-up data.
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.
mesh_terms: D001499:Bayes Theorem; D005500:Follow-Up Studies; D006801:Humans; D007938:Leukemia / Q000401:mortality; D011336:Probability