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DC Field | Value | Language |
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dc.contributor.author | Mavridis, D. | en |
dc.contributor.author | Salanti, G. | en |
dc.date.accessioned | 2015-11-24T19:39:45Z | - |
dc.date.available | 2015-11-24T19:39:45Z | - |
dc.identifier.issn | 1477-0334 | - |
dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/24270 | - |
dc.rights | Default Licence | - |
dc.title | A practical introduction to multivariate meta-analysis | en |
heal.type | journalArticle | - |
heal.type.en | Journal article | en |
heal.type.el | Άρθρο Περιοδικού | el |
heal.identifier.primary | 10.1177/0962280211432219 | - |
heal.identifier.secondary | http://www.ncbi.nlm.nih.gov/pubmed/22275379 | - |
heal.identifier.secondary | http://smm.sagepub.com/content/early/2012/02/16/0962280211432219.full.pdf | - |
heal.language | en | - |
heal.access | campus | - |
heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικής | el |
heal.publicationDate | 2012 | - |
heal.abstract | Multivariate 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.journalName | Stat Methods Med Res | en |
heal.journalType | peer-reviewed | - |
heal.fullTextAvailability | TRUE | - |
Appears in Collections: | Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) - ΙΑΤ |
Files in This Item:
File | Description | Size | Format | |
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Mavridis-2012-A practical introduc.pdf | 285.55 kB | Adobe PDF | View/Open Request a copy |
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