Skip to main content

Bayesian graphical modelling: a case-study in monitoring health outcomes

Buy Article:

$51.00 plus tax (Refund Policy)

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.

Keywords: Cancer incidence; Cervical screening; Gibbs sampling; Hierarchical models; Markov chain Monte Carlo methods

Document Type: Original Article

DOI: http://dx.doi.org/10.1111/1467-9876.00101

Affiliations: Medical Research Council, Biostatistics Unit, Cambridge, UK

Publication date: January 1, 1998

bpl/rssc/1998/00000047/00000001/art00008
dcterms_title,dcterms_description,pub_keyword
6
5
20
40
5

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more