meta: Brief overview of methods and general hints


R package meta is a user-friendly general package providing standard methods for meta-analysis and supporting Schwarzer et al. (2015),


R package meta (Schwarzer, 2007) provides the following meta-analysis methods:

  • fixed effect and random effects meta-analysis (functions metabin, metacont, metacor, metagen, metainc, metaprop, and metarate);

  • several plots (forest, funnel, Galbraith / radial, labbe, baujat, bubble);

  • statistical tests (metabias) and trim-and-fill method (trimfill) to evaluate bias in meta-analysis;

  • import data from 'RevMan 5' (read.rm5; see also metacr);

  • prediction interval, Hartung-Knapp and Paule-Mandel method for random effects model (arguments in meta-analysis functions);

  • 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).

See settings.meta to learn how to print and specify default meta-analysis methods used during your R session. For example, the following R command specifies the use of the Hartung-Knapp and Paule-Mandel methods, and the printing of prediction intervals for any meta-analysis in the current R session:

  • settings.meta(hakn=TRUE, method.tau="PM", prediction=TRUE)

Type help(package = "meta") for a listing of R functions 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 = "meta") if you do not use RStudio,

  • send an email to Guido Schwarzer if you use RStudio.

The development version of meta is available on GitHub


Guido Schwarzer


Schwarzer G (2007), meta: An R package for meta-analysis. R News, 7(3), 40–5.

Schwarzer G, Carpenter JR and Rücker G (2015), Meta-Analysis with R (Use-R!). Springer International Publishing, Switzerland.

Want to suggest features or report bugs for Use the GitHub issue tracker.