Chapter 1 About this Guide

This guide is based on the book ‘Doing Meta-Analysis in R’, by Mathias Harrer, Pim Cuijpers, & David Ebert, and was adapted to focus on the metafor package, and exploring heterogeneity using metaforest. The original can be found here: https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/



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

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. It can be found here.



To get started, proceed to the next chapter!



References

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