A practical introduction to multivariate meta-analysis

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 m...

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Bibliographic Details
Published inStatistical methods in medical research Vol. 22; no. 2; pp. 133 - 158
Main Authors Mavridis, Dimitris, Salanti, Georgia
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.04.2013
Sage Publications Ltd
Subjects
Bayes Theorem
Guidance
Humans
Markov chain Monte Carlo method
Markov Chains
Meta-Analysis as Topic
Monte Carlo Method
Multivariate Analysis
Software
random effects
structural equation models
Bayesian methods
software
correlated outcomes
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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.
AbstractList 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. Adapted from the source document.
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.
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. [PUBLICATION 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.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.
Author Salanti, Georgia
Mavridis, Dimitris
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  surname: Mavridis
  fullname: Mavridis, Dimitris
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  givenname: Georgia
  surname: Salanti
  fullname: Salanti, Georgia
  email: gsalanti@cc.uoi.gr
  organization: Department of Primary Education, University of Ioannina, Ioannina, Greece
BackLink https://www.ncbi.nlm.nih.gov/pubmed/22275379$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
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structural equation models
Bayesian methods
software
correlated outcomes
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Snippet Multivariate meta-analysis is becoming increasingly popular and official routines or self-programmed functions have been included in many statistical software....
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StartPage 133
SubjectTerms Bayes Theorem
Guidance
Humans
Markov chain Monte Carlo method
Markov Chains
Meta-Analysis as Topic
Monte Carlo Method
Multivariate Analysis
Software
Title A practical introduction to multivariate meta-analysis
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