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How to perform a meta-analysis with R: a practical tutorial
Open accessAbstract
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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“Amongst the major modifiable risk factors of stillbirths, risk attributed to malaria is approximately 8% which can be prevented if exposure minimized [30].”
From Malaria in pregnancy: Meta-analyses of prevalence and associated complications (2024) · cites this paper as [30]
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Metadata
- Authors
- Balduzzi, S., Rücker, G., & Schwarzer, G.
- Affiliations
- University of Freiburg (DE)
- Corresponding author
- Balduzzi, Sara
- 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
- 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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