Linked Life Data

11468762

Source:http://linkedlifedata.com/resource/pubmed/id/11468762

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
15
pubmed:dateCreated
2001-7-24
pubmed:abstractText
Meta-analyses are being undertaken in an increasing diversity of diseases and conditions, some of which involve outcomes measured on an ordered categorical scale. We consider methodology for undertaking a meta-analysis on individual patient data for an ordinal response. The approach is based on the proportional odds model, in which the treatment effect is represented by the log-odds ratio. A general framework is proposed for fixed and random effect models. Tests of the validity of the various assumptions made in the meta-analysis models, such as a global test of the assumption of proportional odds between treatments, are presented. The combination of studies with different definitions or numbers of response categories is discussed. The methods are illustrated on two data sets, in a classical framework using SAS and MLn and in a Bayesian framework using BUGS. The relative merits of the three software packages for such meta-analyses are discussed.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0277-6715
pubmed:author
pubmed:copyrightInfo
Copyright 2001 John Wiley & Sons, Ltd.
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
20
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2243-60
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Meta-analysis of ordinal outcomes using individual patient data.
pubmed:affiliation
Medical and Pharmaceutical Statistics Research Unit, The University of Reading, P.O. Box 240, Earley Gate, Reading RG6 6FN, U.K. p.a.whitehead@reading.ac.uk
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't