Welcome to the online version of “Doing Meta-Analysis with R: A Hands-On Guide”.

This book serves as an accessible introduction into how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools.

Advanced, but highly relevant topics such as network meta-analysis, multi-/three-level meta-analyses, Bayesian meta-analysis approaches, and SEM meta-analysis are also covered.

The programming and statistical background covered in the book are kept at a non-expert level. A print version of this book has been published with Chapman & Hall/CRC Press (Taylor & Francis).

Open Source Repository

This book has been built using {rmarkdown} and {bookdown}. Formulas are rendered using MathJax. All materials and source code we used to compile the guide can be found on GitHub. You are free to fork, share and reuse contents. However, the repository is intended to be mainly “read-only”; PRs will generally not be considered (see section below & preface for ways to contact us).

GitHub followers

How To Use The Guide

This tutorial provides a brief introduction to the guide and how to use it for your own meta-analysis project.


This guide is an open source project, and we owe special thanks to our expert contributors who provided additional content in some of the sections of this guide.

Want to contribute to this guide yourself? Feel free to send Mathias () an E-mail and tell us about your proposed additions.

Citing this Guide

The suggested citation is:

Harrer, M., Cuijpers, P., Furukawa, T.A., & Ebert, D.D. (2021). Doing Meta-Analysis with R: A Hands-On Guide. Boca Raton, FL and London: Chapman & Hall/CRC Press. ISBN 978-0-367-61007-4.

Download the reference as BibTeX or .ris.

Cite the Packages

In this guide, we present and use various R packages. The reason why all of us can use these packages for free is because experts all around the world have devoted enormous time and effort to their development, typically without pay. If you use some of the packages mentioned in this book for your own meta-analysis, we strongly encourage you to also cite them in your report.

In this guide, every time a new package is introduced, we also provide the reference through which it can be cited. It is also possible to run citation("package") to retrieve the preferred reference. Thanks!