Chapter 1 About this Guide

This guide shows you how to conduct Meta-Analyses in R from scratch. The focus of this guide is primarily on clinical outcome research in psychology. It is designed for staff and collaborators of the PROTECT Lab, which is headed by Dr. David D. Ebert.

The guide will show you how to:

  • Get R and RStudio set for your Meta-Analysis
  • Get your data into R
  • Prepare your data for the meta-analysis
  • Perform fixed-effect and random-effects meta-analysis using the meta and metaforpackages
  • Analyse the heterogeneity of your results
  • Tackle heterogeneity using subgroup analyses and meta-regression
  • Check if selective outcome reporting (publication bias) is a present in your data
  • Control for selective outcome reporting and publication bias
  • Analyse the risk of bias in your data
  • Do advanced types of meta-analyses, such as
    • network analyses or
    • meta-analyses with more than one outcome

What this guide will not cover

Although this guide will provide some information on the statistics behind meta-analysis, it will not give you an in-depth introduction into how meta-analyses are calculated statistically.

It is also beyond the scope of this guide to advise in detail which meta-analytical strategy is suited best in which contexts, and on how the search, study inclusion and reporting of meta-analyses should be conducted. The Cochrane Handbook for Systematic Reviews of Interventions, however, should be a great source to find more information on these topics.

Generally, there a two other sources to recommended when conducting Meta-Analyses:

  • If you’re looking for a easily digestable, hands-on introduction on how Meta-Analyses are conducted, we can recommend Pim Cuijpers’ online courses on Meta-Analysis. The courses are freely available on YouTube. To have a look, click here.
  • If you’re interested in more details on how to conduct Meta-Analyses in R, you can either have a look at Wolfgang Viechtbauer’s page for the metafor package (Link). Or you can consult a book on the meta package which was recently published (Schwarzer, Carpenter, and Rücker 2015).

How to get the R code for this guide

All code behind this book is available online on GitHub. We have created a website containing a download link for all codes, and a quick guide on how to get the code running on your computer. The site can be found here.

How to cite this guide

Harrer, M. & Ebert, D. D. (2018). Doing Meta-Analysis in R: A practical Guide. PROTECT Lab Friedrich-Alexander University Erlangen-Nuremberg.

To get started, proceed to the next chapter!


Schwarzer, Guido, James R Carpenter, and Gerta Rücker. 2015. Meta-Analysis with R. Springer.