A contrast of meta and metafor packages for meta-analyses in R

1 Biology, YorkU, Toronto, Canada
2 UCSB, The National Center for Ecological Analysis and Synthesis, Santa Barbara, CA, USA
DOI
10.7287/peerj.preprints.27608v1
Published
Accepted
Subject Areas
Computational Biology, Data Science
Keywords
programming language, R language, metafor, meta, meta-analysis, synthesis, useability, complexity, open science
Copyright
© 2019 Lortie
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Lortie CJ. 2019. A contrast of meta and metafor packages for meta-analyses in R. PeerJ Preprints 7:e27608v1

Abstract

There is extensive support and choice in R to support meta-analyses. Two common packages in the natural sciences include meta and metafor. Here, a brief contrast of the strengths of each is described for the synthesis scientist. Meta is a direct, intuitive choice for rapid implementation of general meta-analytical statistics. Metafor is a comprehensive package for analyses if the fit models are more complex. Both packages provide estimates of heterogeneity, excellent visualization tools, and functions to explore publication bias. Preference and critical outcomes can facilitate choice between these two specific options. Nonetheless, metafor has a steeper learning curve but greater rewards.

Author Comment

This ms is submitted to R Journal for review.