Description Details Author(s) References
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:
Forest plot (forest
)
Funnel plot (funnel
)
Galbraith plot / radial plot (radial
)
L'Abbe plot for meta-analysis with binary outcome data (labbe
)
Baujat plot to explore heterogeneity in meta-analysis (baujat
)
Bubble plot to display the result of a meta-regression (bubble
)
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
); if R packages metafor, lme4,
numDeriv, and BiasedUrn are installed
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 [email protected] if you use RStudio.
The development version of meta is available on GitHub https://github.com/guido-s/meta.
Guido Schwarzer [email protected]
Schwarzer G (2007), meta: An R package for meta-analysis. R News, 7(3), 40–5. https://cran.r-project.org/doc/Rnews/Rnews_2007-3.pdf
Schwarzer G, Carpenter JR and Rücker G (2015), Meta-Analysis with R (Use-R!). Springer International Publishing, Switzerland. http://www.springer.com/gp/book/9783319214153
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