R package meta is a user-friendly general package providing standard methods for meta-analysis and supporting Schwarzer et al. (2015), http://meta-analysis-with-r.org/.
R package meta (Schwarzer, 2007) provides the following statistical methods for meta-analysis.
Fixed effect and random effects model:
Meta-analysis of continuous outcome data (metacont)
Meta-analysis of binary outcome data (metabin)
Meta-analysis of incidence rates (metainc)
Generic inverse variance meta-analysis (metagen)
Meta-analysis of single correlations (metacor)
Meta-analysis of single means (metamean)
Meta-analysis of single proportions (metaprop)
Meta-analysis of single incidence rates (metarate)
Several plots for meta-analysis:
Statistical tests for funnel plot asymmetry
(metabias) and trim-and-fill method
(trimfill) to evaluate bias in meta-analysis
Import data from 'RevMan 5' (read.rm5); see
also metacr to conduct meta-analysis for a single
comparison and outcome from a Cochrane review
Prediction interval, Hartung-Knapp and Paule-Mandel method
for random effects model (see arguments prediction,
hakn, and method.tau, respectively, in
meta-analysis functions listed under 1. Fixed effect and
random effects model)
Cumulative meta-analysis (metacum) and
leave-one-out meta-analysis (metainf)
Meta-regression (metareg); if R package
metafor is installed
Generalised linear mixed models (metabin,
metainc, metaprop, and
metarate)
The following more advanced statistical methods are provided by add-on R packages:
Frequentist methods for network meta-analysis (R package netmeta)
Advanced methods to model and adjust for bias in meta-analysis (R package metasens)
Results of several meta-analyses can be combined with
metabind. This is, for example, useful to generate a
forest plot with results of subgroup analyses.
See settings.meta to learn how to print and specify
default meta-analysis methods used during your R session. For
example, the function can be used to specify general settings:
settings.meta("revman5")
settings.meta("jama")
The first command can be used to reproduce meta-analyses from Cochrane reviews conducted with Review Manager 5 (RevMan 5, http://community.cochrane.org/tools/review-production-tools/revman-5) and specifies to use a RevMan 5 layout in forest plots. The second command can be used to generate forest plots following instructions for authors of the Journal of the American Medical Association (http://jamanetwork.com/journals/jama/pages/instructions-for-authors).
In addition, settings.meta can be used to change
individual settings. For example, the following R command specifies
the use of the Hartung-Knapp and Paule-Mandel methods, and the
printing of prediction intervals in the current R session for any
meta-analysis generated after execution of this command:
settings.meta(hakn=TRUE, method.tau="PM", prediction=TRUE)
Type help(package = "meta") for a listing of R functions and
datasets available in meta.
Schwarzer (2007) is the preferred citation in publications for
meta. Type citation("meta") for a BibTeX entry of
this publication.
To report problems and bugs
type bug.report(package = "meta") if you do not use
RStudio,
send an email to Guido Schwarzer sc@imbi.uni-freiburg.de if you use RStudio.
The development version of meta is available on GitHub https://github.com/guido-s/meta.
Schwarzer G (2007): meta: An R package for meta-analysis. R News, 7, 40--5
Schwarzer G, Carpenter JR and R<U+00FC>cker G (2015): Meta-Analysis with R (Use-R!). Springer International Publishing, Switzerland