English language
Published 2021 by Taylor & Francis Group.
Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and 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. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible.
I didn't knew much about meta-analysis and I learned a lot in this book. But I also realize now that I'm trying to apply this knowledge to a concrete case that I miss some bit of information (in particular: what to do when the results are not reported as a simple t-test or a correlation?). A good entrance point nevertheless!
