Linked Life Data

8981683

Source:http://linkedlifedata.com/resource/pubmed/id/8981683

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
24
pubmed:dateCreated
1997-3-11
pubmed:abstractText
There exists a variety of situations in which a random effects meta-analysis might be undertaken using a small number of clinical trials. A problem associated with small meta-analyses is estimating the heterogeneity between trials. To overcome this problem, information from other related studies may be incorporated into the meta-analysis. A Bayesian approach to this problem is presented using data from previous meta-analyses in the same therapeutic area to formulate a prior distribution for the heterogeneity. The treatment difference parameters are given non-informative priors. Further, related trials which compare one or other of the treatments of interest with a common third treatment are included in the model to improve inference on both the heterogeneity and the treatment difference. Two approaches to estimating relative efficacy are considered, namely a general parametric approach and a method explicit to binary data. The methodology is illustrated using data from 26 clinical trials which investigate the prevention of cirrhosis using beta-blockers and sclerotherapy. Both sources of external information lead to more precise posterior distributions for all parameters, in particular that representing heterogeneity.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0277-6715
pubmed:author
pubmed:issnType
Print
pubmed:day
30
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2733-49
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
1996
pubmed:articleTitle
Borrowing strength from external trials in a meta-analysis.
pubmed:affiliation
Department of Applied Statistics, University of Reading, U.K.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't