Cited by 5,827Meta-analysis and systematic reviewsData Analysis with RStatistical Methods in Epidemiology

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

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Balduzzi, Sara, Rücker, Gerta, Schwarzer, Guido·2019·Evidence Based Mental Health

DOI 10.1136/ebmental-2019-300117PMC PMC10231495

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Abstract

OBJECTIVE: Meta-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. METHODS: R 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. RESULTS: The 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. CONCLUSIONS: R 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.

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Authors: Balduzzi, S., Rücker, G., & Schwarzer, G.
Affiliations: University of Freiburg (DE)
Corresponding author: Balduzzi, Sara
ORCID: Balduzzi, Sara
Rücker, Gerta
Schwarzer, Guido
Venue: Evidence Based Mental Health
Publisher: BMJ
Published: 2019-09-28
Volume: 22
Issue: 4
Pages: 153-160
ISSN: 1362-0347 (ISSN-L)
1468-960X
DOI: 10.1136/ebmental-2019-300117
PMC: PMC10231495
OpenAlex: W2975424845
Cited by: 5,827
References: 31
Citations by year: 2026: 1019 · 2025: 1163 · 2024: 1107 · 2023: 876 · 2022: 885 · 2021: 574 · 2020: 200
FWCI: 84.22
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Evidence-Based Mental Health (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
HighWire Press Open Archive (submittedVersion)
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Data Analysis with R
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords: meta-analysis, R software, meta-package, sensitivity analysis, selection bias, fixed effects model, random effects models, subgroup analysis, forest plots, funnel plot asymmetry, binary outcomes, mental health research
MeSH terms: Humans, Software, Meta-Analysis as Topic, Biomedical Research

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