Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/21804
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dc.contributor.authorSalanti, G.en
dc.contributor.authorHiggins, J. P.en
dc.contributor.authorAdes, A. E.en
dc.contributor.authorIoannidis, J. P.en
dc.date.accessioned2015-11-24T19:17:44Z-
dc.date.available2015-11-24T19:17:44Z-
dc.identifier.issn0962-2802-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/21804-
dc.rightsDefault Licence-
dc.subjectHumansen
dc.subject*Meta-Analysis as Topicen
dc.subject*Models, Statisticalen
dc.subjectRandomized Controlled Trials as Topic/methods/*statistics & numerical dataen
dc.subjectResearch Design/statistics & numerical dataen
dc.titleEvaluation of networks of randomized trialsen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primary10.1177/0962280207080643-
heal.identifier.secondaryhttp://www.ncbi.nlm.nih.gov/pubmed/17925316-
heal.identifier.secondaryhttp://smm.sagepub.com/content/17/3/279.full.pdf-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικήςel
heal.publicationDate2008-
heal.abstractRandomized trials may be designed and interpreted as single experiments or they may be seen in the context of other similar or relevant evidence. The amount and complexity of available randomized evidence vary for different topics. Systematic reviews may be useful in identifying gaps in the existing randomized evidence, pointing to discrepancies between trials, and planning future trials. A new, promising, but also very much debated extension of systematic reviews, mixed treatment comparison (MTC) meta-analysis, has become increasingly popular recently. MTC meta-analysis may have value in interpreting the available randomized evidence from networks of trials and can rank many different treatments, going beyond focusing on simple pairwise-comparisons. Nevertheless, the evaluation of networks also presents special challenges and caveats. In this article, we review the statistical methodology for MTC meta-analysis. We discuss the concept of inconsistency and methods that have been proposed to evaluate it as well as the methodological gaps that remain. We introduce the concepts of network geometry and asymmetry, and propose metrics for the evaluation of the asymmetry. Finally, we discuss the implications of inconsistency, network geometry and asymmetry in informing the planning of future trials.en
heal.journalNameStat Methods Med Resen
heal.journalTypepeer-reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) - ΙΑΤ

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