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dc.contributor.authorMavridis, D.en
dc.contributor.authorSalanti, G.en
dc.date.accessioned2015-11-24T19:39:45Z-
dc.date.available2015-11-24T19:39:45Z-
dc.identifier.issn1477-0334-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/24270-
dc.rightsDefault Licence-
dc.titleA practical introduction to multivariate meta-analysisen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primary10.1177/0962280211432219-
heal.identifier.secondaryhttp://www.ncbi.nlm.nih.gov/pubmed/22275379-
heal.identifier.secondaryhttp://smm.sagepub.com/content/early/2012/02/16/0962280211432219.full.pdf-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικήςel
heal.publicationDate2012-
heal.abstractMultivariate meta-analysis is becoming increasingly popular and official routines or self-programmed functions have been included in many statistical software. In this article, we review the statistical methods and the related software for multivariate meta-analysis. Emphasis is placed on Bayesian methods using Markov chain Monte Carlo, and codes in WinBUGS are provided. The various model-fitting options are illustrated in two examples and specific guidance is provided on how to run a multivariate meta-analysis using various software packages.en
heal.journalNameStat Methods Med Resen
heal.journalTypepeer-reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) - ΙΑΤ

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