Meta-Analysis with R

by Guido Schwarzer, James R. Carpenter, Gerta Rücker

This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.

264 pages, Kindle Edition

Published October 8, 2015

Reviews

[Arifudin Achmad · Rating 5 out of 5]

A great and concise book for anyone who wants to conduct any type of meta-analysis with R according to the state-of-the-art methods. It took me only three days to grab the R script writing provided in this book, from almost zero with R programming. Highly recommended.
Note: Of course this book will not teach you how to do little things like data preparation in R. Spare a little time on DataCamp and finish their introduction course before jump into this book!

[Sergio Uribe · Rating 4 out of 5]

UPDATE: after having done my first meta-analisis in R, I found this book really useful. The meta package is almost everything you need to do all the calculations, hence a four star book. The missing star is for the graphs. This is not really an issue of the book, but would be useful to have more information about how to create high quality plots for ma.


This book focuses only in the meta package and only in calculations. Doesn't have much information about heterogeneity analysis none about graphs.

The information about the calculations of the meta package are detailed.

So, the title should be "Meta-analysis in R with the meta-package".

Another package useful is metafor.