| pubmed-article:8981683 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:8981683 | lifeskim:mentions | umls-concept:C0008976 | lld:lifeskim |
| pubmed-article:8981683 | lifeskim:mentions | umls-concept:C0920317 | lld:lifeskim |
| pubmed-article:8981683 | lifeskim:mentions | umls-concept:C0205101 | lld:lifeskim |
| pubmed-article:8981683 | lifeskim:mentions | umls-concept:C0808080 | lld:lifeskim |
| pubmed-article:8981683 | lifeskim:mentions | umls-concept:C1705922 | lld:lifeskim |
| pubmed-article:8981683 | pubmed:issue | 24 | lld:pubmed |
| pubmed-article:8981683 | pubmed:dateCreated | 1997-3-11 | lld:pubmed |
| pubmed-article:8981683 | 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. | lld:pubmed |
| pubmed-article:8981683 | pubmed:language | eng | lld:pubmed |
| pubmed-article:8981683 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:8981683 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:8981683 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:8981683 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:8981683 | pubmed:month | Dec | lld:pubmed |
| pubmed-article:8981683 | pubmed:issn | 0277-6715 | lld:pubmed |
| pubmed-article:8981683 | pubmed:author | pubmed-author:WhiteheadAA | lld:pubmed |
| pubmed-article:8981683 | pubmed:author | pubmed-author:HigginsJ PJP | lld:pubmed |
| pubmed-article:8981683 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:8981683 | pubmed:day | 30 | lld:pubmed |
| pubmed-article:8981683 | pubmed:volume | 15 | lld:pubmed |
| pubmed-article:8981683 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:8981683 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:8981683 | pubmed:pagination | 2733-49 | lld:pubmed |
| pubmed-article:8981683 | pubmed:dateRevised | 2007-11-15 | lld:pubmed |
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| pubmed-article:8981683 | pubmed:meshHeading | pubmed-meshheading:8981683-... | lld:pubmed |
| pubmed-article:8981683 | pubmed:year | 1996 | lld:pubmed |
| pubmed-article:8981683 | pubmed:articleTitle | Borrowing strength from external trials in a meta-analysis. | lld:pubmed |
| pubmed-article:8981683 | pubmed:affiliation | Department of Applied Statistics, University of Reading, U.K. | lld:pubmed |
| pubmed-article:8981683 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:8981683 | pubmed:publicationType | Comparative Study | lld:pubmed |
| pubmed-article:8981683 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
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