How to perform a meta-analysis with R: a practical tutorial

ObjectiveMeta-analysis is of fundamental importance to obtain an unbiased assessment of the available evidence. In general, the use of meta-analysis has been increasing over the last three decades with mental health as a major research topic. It is then essential to well understand its methodology a...

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Bibliographic Details
Published in:BMJ Mental Health 2019-11, Vol.22 (4), p.153-160
Main Authors: Balduzzi, Sara, Rücker, Gerta, Schwarzer, Guido
Format: Article
Language:English
Subjects:
Bias
Datasets
Libraries
Mental health
Meta-analysis
Methods
Schizophrenia
Software
Statistical analysis
Statistics in Practice
Systematic review
Variables
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Summary:ObjectiveMeta-analysis is of fundamental importance to obtain an unbiased assessment of the available evidence. In general, the use of meta-analysis has been increasing over the last three decades with mental health as a major research topic. It is then essential to well understand its methodology and interpret its results. In this publication, we describe how to perform a meta-analysis with the freely available statistical software environment R, using a working example taken from the field of mental health.MethodsR package meta is used to conduct standard meta-analysis. Sensitivity analyses for missing binary outcome data and potential selection bias are conducted with R package metasens. All essential R commands are provided and clearly described to conduct and report analyses.ResultsThe working example considers a binary outcome: we show how to conduct a fixed effect and random effects meta-analysis and subgroup analysis, produce a forest and funnel plot and to test and adjust for funnel plot asymmetry. All these steps work similar for other outcome types.ConclusionsR represents a powerful and flexible tool to conduct meta-analyses. This publication gives a brief glimpse into the topic and provides directions to more advanced meta-analysis methods available in R.
ISSN:1362-0347
2755-9734
1468-960X
DOI:10.1136/ebmental-2019-300117