Linked Life Data

19408255

Source:http://linkedlifedata.com/resource/pubmed/id/19408255

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2010-5-25
pubmed:abstractText
Multivariate meta-analysis is increasingly used in medical statistics. In the univariate setting, the non-iterative method proposed by DerSimonian and Laird is a simple and now standard way of performing random effects meta-analyses. We propose a natural and easily implemented multivariate extension of this procedure which is accessible to applied researchers and provides a much less computationally intensive alternative to existing methods. In a simulation study, the proposed procedure performs similarly in almost all ways to the more established iterative restricted maximum likelihood approach. The method is applied to some real data sets and an extension to multivariate meta-regression is described.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1097-0258
pubmed:author
pubmed:copyrightInfo
Copyright (c) 2009 John Wiley & Sons, Ltd.
pubmed:issnType
Electronic
pubmed:day
30
pubmed:volume
29
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1282-97
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Extending DerSimonian and Laird's methodology to perform multivariate random effects meta-analyses.
pubmed:affiliation
MRC Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 0SR, UK. daniel.jackson@mrc-bsu.cam.ac.uk
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't