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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mavridis, D. | en |
dc.contributor.author | Salanti, G. | en |
dc.date.accessioned | 2015-11-24T17:44:51Z | - |
dc.date.available | 2015-11-24T17:44:51Z | - |
dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/14956 | - |
dc.rights | Default Licence | - |
dc.subject | Bayesian methods, correlated outcomes, random effects, software, structural equation models | en |
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://smm.sagepub.com/content/early/2012/01/23/0962280211432219.full.pdf+html | - |
heal.language | en | - |
heal.access | campus | - |
heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Αγωγής. Παιδαγωγικό Τμήμα Δημοτικής Εκπαίδευσης | 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 modelfitting 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 | Statistical Methods in Medical Research | en |
heal.journalType | peer-reviewed | - |
heal.fullTextAvailability | TRUE | - |
Appears in Collections: | Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) |
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File | Description | Size | Format | |
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mavridis-2012-A practical introduction.pdf | 441.57 kB | Adobe PDF | View/Open Request a copy |
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