Bayesian graphical modelling: a case-study in monitoring health outcomes
Abstract:Bayesian graphical modelling represents the synthesis of several recent developments in applied complex modelling. After describing a moderately challenging real example, we show how graphical models and Markov chain Monte Carlo methods naturally provide a direct path between model specification and the computational means of making inferences on that model. These ideas are illustrated with a range of modelling issues related to our example. An appendix discusses the BUGS software.
Document Type: Original Article
Affiliations: Medical Research Council, Biostatistics Unit, Cambridge, UK
Publication date: January 1, 1998