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index.Rmd
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---
title: "Doing Meta-Analysis in R"
subtitle: "A Hands-on Guide"
author:
- Mathias Harrer, M.Sc.¹
- Prof. Dr. Pim Cuijpers²
- Prof. Dr. Toshi A. Furukawa³
- Assoc. Prof. Dr. David D. Ebert²
date: "¹Friedrich-Alexander-University Erlangen-Nuremberg, ²Vrije Universiteit Amsterdam, ³Kyoto University"
github-repo: "MathiasHarrer/Doing-Meta-Analysis-in-R"
site: bookdown::bookdown_site
output:
bookdown::gitbook:
config:
toc:
collapse: section
search: yes
fontsettings:
size: 2
split_by: section
includes:
after_body: banner.html
df_print: paged
documentclass: book
bibliography: [book.bib, packages.bib]
biblio-style: apalike
link-citations: yes
description: "This is a guide on how to conduct Meta-Analyses in R."
favicon: "favicon.ico"
---
# (PART) Introduction & R Basics {-}
# About this Guide
![](_figs/coverbild.jpg)
```{block,type='rmdinfo'}
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 was designed for staff and collaborators of the [**Protect Lab**](https://www.protectlab.org), which is headed by **Prof. Dr. David D. Ebert**.
```
<br></br>
<img width="40%" src="_figs/protectlogo.PNG"/>
<img width="15%" src="_figs/hexagon.png"/>
---
#### 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.
* Install and use the `dmetar` *R* package we built specifically for this guide.
* Perform **fixed-effect** and **random-effects** meta-analysis using the `meta` and `metafor` packages.
* Analyse the **heterogeneity** of your results.
* Tackle heterogeneity using **subgroup analyses** and **meta-regression**.
* Check if **selective outcome reporting (publication bias)** or $p$**-hacking** is present in your data.
* Summarize the **risk of bias** of your study material.
* Calculate the **power** of a meta-analysis.
* **Convert effect sizes** reported in original studies to the ones you need for your meta-analysis.
* Do advanced types of meta-analyses, such as
+ **multilevel meta-analyses**
+ **multivariate meta-analyses**
+ **meta-analytic structural equation modeling** or
+ **network meta-analyses**.
---
#### 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*](http://handbook-5-1.cochrane.org/), however, should be a great source to find more information on these topics.
---
#### Other sources to recommend when conducting Meta-Analyses {-}
* If you are looking for an 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](https://www.youtube.com/watch?v=pP7_VBrG_TY&list=PL-h5cI5Bkvt0J-O0kq_9J9_aksWFPgR7s). The course is based on a **book** [@cuijpers2016meta], which you can download for free [here](http://bit.do/meta-analysis).
* If you are interested in more details on how to conduct meta-analyses in *R*, you can either have a look at Wolfgang Viechtbauer's webpage for the `metafor` package ([Link](http://metafor-project.org)). Or you can consult a book written by Schwarzer and colleagues on the `meta` package [@schwarzer2015meta]. We can also recommend a book written by **Terri Pigott**, which focuses more on the theoretical background of and advances in meta-analytic techniques [@pigott2012advances].
<br><br>
````{block,type='rmdinfo'}
**How to get the R code for this guide**
![](_figs/githublogo.png)
All code behind this book is available online on **GitHub**. We have created a website containing a **download link** for all material, and a **quick guide** on how to get the *R* code presented in this book running on your computer. The site can be found [here](https://mathiasharrer.github.io/Doing-Meta-Analysis-in-R/).
```
<br><br>
#### How to cite this guide {-}
Harrer, M., Cuijpers, P., Furukawa, T.A, & Ebert, D. D. (2019). Doing Meta-Analysis in R: A Hands-on Guide. [https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/](https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/).
[![DOI](https://zenodo.org/badge/152492192.svg)](https://zenodo.org/badge/latestdoi/152492192). [Citation Download](www.protectlab.org/meta-analysis-in-r)
```{r eval=FALSE, echo=FALSE}
install.packages("bookdown")
# or the development version
# devtools::install_github("rstudio/bookdown")
```
---
**To get started, proceed to the next chapter!**
---
### License {-}
<a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc/4.0/88x31.png" /></a><br /><span xmlns:dct="http://purl.org/dc/terms/" property="dct:title">Doing Meta-Analysis in R: A Hands-On Guide</span> by <a xmlns:cc="http://creativecommons.org/ns#" href="https://github.com/MathiasHarrer/Doing-Meta-Analysis-in-R" property="cc:attributionName" rel="cc:attributionURL">Mathias Harrer, Pim Cuijpers, Toshi Furukawa and David Ebert</a> is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/">Creative Commons Attribution-NonCommercial 4.0 International License</a>.
$$~$$
### Contributors {-}
This guide is an open project, and we owe special thanks to our expert contributors who provided additional content in some of the sections of this guide.
* [**Luke A. McGuinness, M.Sc.**](https://twitter.com/mcguinlu), University of Bristol: Chapter 10, Risk of Bias Plots.
Want to contribute to this guide yourself? Feel free to send **Mathias** ([email protected]) an E-mail and tell us about your proposed additions.
<br><br>
```{r include=FALSE}
# automatically create a bib database for R packages
knitr::write_bib(c(
.packages(), 'bookdown', 'knitr', 'rmarkdown'
), 'packages.bib')
```