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...

Full description

Saved in:
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
Online AccessGet full text

Cover

More Information
Summary: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.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0962-2802
1477-0334
1477-0334
DOI:10.1177/0962280211432219