metafor

Meta-Analysis Package for R

A comprehensive collection of functions for conducting meta-analyses in R. The package includes functions to calculate various effect sizes or outcome measures, fit fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots (e.g., forest, funnel, radial, L'Abbe, Baujat, GOSH plots). For meta-analyses of binomial and person-time data, the package also provides functions that implement specialized methods, including the Mantel-Haenszel method, Peto's method, and a variety of suitable generalized linear (mixed-effects) models (i.e., mixed-effects logistic and Poisson regression models). Finally, the package provides functionality for fitting meta-analytic multivariate/multilevel models that account for non-independent sampling errors and/or true effects (e.g., due to the inclusion of multiple treatment studies, multiple endpoints, or other forms of clustering). Network meta-analyses and meta-analyses accounting for known correlation structures (e.g., due to phylogenetic relatedness) can also be conducted.

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Description file content

Package
metafor
Version
2.0-0
Date
2017-06-22
Title
Meta-Analysis Package for R
Depends
R (>= 3.2.0), methods, Matrix
Imports
stats, utils, graphics, grDevices, nlme
Suggests
lme4, numDeriv, minqa, nloptr, dfoptim, ucminf, CompQuadForm, mvtnorm, Formula, R.rsp, testthat, BiasedUrn, survival, Epi, multcomp, gsl, boot, MASS
Description
A comprehensive collection of functions for conducting meta-analyses in R. The package includes functions to calculate various effect sizes or outcome measures, fit fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots (e.g., forest, funnel, radial, L'Abbe, Baujat, GOSH plots). For meta-analyses of binomial and person-time data, the package also provides functions that implement specialized methods, including the Mantel-Haenszel method, Peto's method, and a variety of suitable generalized linear (mixed-effects) models (i.e., mixed-effects logistic and Poisson regression models). Finally, the package provides functionality for fitting meta-analytic multivariate/multilevel models that account for non-independent sampling errors and/or true effects (e.g., due to the inclusion of multiple treatment studies, multiple endpoints, or other forms of clustering). Network meta-analyses and meta-analyses accounting for known correlation structures (e.g., due to phylogenetic relatedness) can also be conducted.
License
GPL (>= 2)
ByteCompile
TRUE
LazyData
TRUE
Encoding
UTF-8
VignetteBuilder
R.rsp
URL
BugReports
https://github.com/wviechtb/metafor/issues
NeedsCompilation
no
Packaged
2017-06-22 12:10:06 UTC; Wolfgang
Author
Wolfgang Viechtbauer [aut, cre]
Maintainer
Wolfgang Viechtbauer
Repository
CRAN
Date/Publication
2017-06-22 13:56:47 UTC

install.packages('metafor')

2.0-0

a year ago

http://www.metafor-project.org

Wolfgang Viechtbauer

GPL (>= 2)

Depends on

R (>= 3.2.0), methods, Matrix

Imports

stats, utils, graphics, grDevices, nlme

Suggests

lme4, numDeriv, minqa, nloptr, dfoptim, ucminf, CompQuadForm, mvtnorm, Formula, R.rsp, testthat, BiasedUrn, survival, Epi, multcomp, gsl, boot, MASS

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