Linked Life Data

12602771

Source:http://linkedlifedata.com/resource/pubmed/id/12602771

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2003-2-26
pubmed:abstractText
There has been much recent work on Bayesian approaches to survival analysis, incorporating features such as flexible baseline hazards, time-dependent covariate effects, and random effects. Some of the proposed methods are quite complicated to implement, and we argue that as good or better results can be obtained via simpler methods. In particular, the normal approximation to the log-gamma distribution yields easy and efficient computational methods in the face of simple multivariate normal priors for baseline log-hazards and time-dependent covariate effects. While the basic method applies to piecewise-constant hazards and covariate effects, it is easy to apply importance sampling to consider smoother functions.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1380-7870
pubmed:author
pubmed:issnType
Print
pubmed:volume
9
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
5-19
pubmed:dateRevised
2005-11-16
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
A simple approach to fitting Bayesian survival models.
pubmed:affiliation
Department of Statistics, University of British Columbia, Vancouver, BC, Canada. gustaf@stat.ubc.ca
pubmed:publicationType
Journal Article, Review