https://github.com/guido-s/netmeta
Official Git repository of R package netmeta
https://github.com/guido-s/netmeta
cran meta-analysis network-meta-analysis r rstudio
Last synced: over 1 year ago
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Official Git repository of R package netmeta
- Host: GitHub
- URL: https://github.com/guido-s/netmeta
- Owner: guido-s
- License: other
- Created: 2015-02-10T16:18:34.000Z (over 11 years ago)
- Default Branch: develop
- Last Pushed: 2025-03-21T18:16:03.000Z (over 1 year ago)
- Last Synced: 2025-03-29T10:05:06.131Z (over 1 year ago)
- Topics: cran, meta-analysis, network-meta-analysis, r, rstudio
- Language: R
- Homepage: http://cran.r-project.org/web/packages/netmeta/index.html
- Size: 3.37 MB
- Stars: 33
- Watchers: 9
- Forks: 14
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md
- License: COPYING
Awesome Lists containing this project
README
# netmeta: Network Meta-Analysis using Frequentist Methods
Official Git repository of R package **netmeta**
[](https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html)
[](https://cran.r-project.org/package=netmeta)
[](https://img.shields.io/badge/develop-3.2--0-purple)
[](https://cranlogs.r-pkg.org/badges/netmeta)
[](https://cranlogs.r-pkg.org/badges/grand-total/netmeta)
## Authors
[Gerta Rücker](https://orcid.org/0000-0002-2192-2560),
Ulrike Krahn,
[Jochem König](https://orcid.org/0000-0003-4683-0360),
[Orestis Efthimiou](https://orcid.org/0000-0002-0955-7572),
[Annabel Davies](https://orcid.org/0000-0003-2320-7701),
[Theodoros Papakonstantinou](https://orcid.org/0000-0002-6630-6817),
[Guido Schwarzer](https://orcid.org/0000-0001-6214-9087)
## Contributors
[Theodoros Evrenoglou](https://orcid.org/0000-0003-3336-8058),
[Krzysztof Ciomek](https://orcid.org/0000-0002-2293-2146)
## Description
R package **netmeta** ([Balduzzi et al., 2023](https://www.doi.org/10.18637/jss.v106.i02)) provides frequentist methods for network meta-analysis and supports [Schwarzer et al. (2015)](https://link.springer.com/book/10.1007/978-3-319-21416-0), Chapter 8 "Network Meta-Analysis".
### Available network meta-analysis models
- frequentist network meta-analysis ([Rücker, 2012](https://scholar.google.com/scholar?q=Rücker+2012+Network+meta-analysis+electrical+networks+and+graph+theory); [Rücker & Schwarzer, 2014](https://scholar.google.com/scholar?q=Rücker+Schwarzer+2014+Reduce+dimension+or+reduce+weights));
- additive network meta-analysis for combinations of treatments
([Rücker, Petropoulou et al.,
2020](https://doi.org/10.1002/bimj.201800167));
- network meta-analysis of binary data using the Mantel-Haenszel
method or the non-central hypergeometric distribution ([Efthimiou
et al.,
2019](https://scholar.google.com/scholar?q=Efthimiou+Rücker+Schwarzer+Higgins+Egger+Salanti+2019+Mantel-Haenszel+model)),
or penalised logistic regression ([Evrenoglou et al.,
2022](https://doi.org/10.1002/sim.9562)).
### Methods to present results of a network meta-analysis
- network graphs ([Rücker & Schwarzer,
2016](https://scholar.google.com/scholar?q=Rücker+Schwarzer+2016+Automated+drawing+of+network+plots+in+network+meta-analysis));
- forest plots;
- league tables with network meta-analysis results;
- tables with network, direct and indirect estimates looking similar to the statistical part of a GRADE table for a network meta-analysis ([Puhan et al., 2014](https://scholar.google.com/scholar?q=puhan+schünemann+murad+2014+grade+network+meta-analysis)).
### Methods to rank treatments
- rankograms and ranking by the Surface Under the Cumulative RAnking curve (SUCRA) ([Salanti et al., 2011](https://scholar.google.com/scholar?q=salanti+ades+ioannidis+2011+graphical+methods+multiple-treatment+meta-analysis));
- ranking of treatments by P-scores (frequentist analogue of SUCRAs without resampling)
([Rücker & Schwarzer,
2015](https://doi.org/10.1186/s12874-015-0060-8));
- partial order of treatment rankings ('poset') and Hasse diagram
for 'poset' ([Carlsen & Bruggemann,
2014](https://scholar.google.com/scholar?q=Partial+order+methodology%3A+a+valuable+tool+in+chemometrics);
[Rücker & Schwarzer,
2017](https://scholar.google.com/scholar?q=Rücker+Schwarzer+2017+resolve+conflicting+rankings+of+outcomes+in+network+meta-analysis)).
### Methods to evaluate network inconsistency
- split direct and indirect evidence to check consistency ([Dias et
al.,
2010](https://scholar.google.com/scholar?q=Checking+consistency+in+mixed+treatment+comparison+meta-analysis));
- net heat plot and design-based decomposition of Cochran's Q
([Krahn et al., 2013](https://doi.org/10.1186/1471-2288-13-35)).
### Additional methods
- contribution of direct comparisons to network estimates ([Papakonstantinou et al.,
2018](https://doi.org/10.12688/f1000research.14770.3); [Davies et al., 2022](https://doi.org/10.1002/sim.9346))
- importance of individual studies measured by reduction of precision if removed from network ([Rücker, Nikolakopoulou et al., 2020](https://doi.org/10.1186/s12874-020-01075-y))
- 'comparison-adjusted' funnel plot ([Chaimani & Salanti,
2012](https://scholar.google.com/scholar?q=Chaimani+Salanti+Using+network+meta-analysis+to+evaluate+the+existence+of+small-study+effects+in+a+network+of+interventions));
- measures characterizing the flow of evidence between two
treatments ([König et al.,
2013](https://scholar.google.com/scholar?q=König+Krahn+Binder+2013+Visualizing+the+flow+of+evidence+in+network+meta-analysis+and+characterizing+mixed+treatment+comparisons)).
## Installation
### Current official [](https://cran.r-project.org/package=netmeta) release:
```r
install.packages("netmeta")
```
### Current [](https://img.shields.io/badge/develop-3.2--0-purple) release on GitHub:
Installation using R package
[**remotes**](https://cran.r-project.org/package=remotes):
```r
install.packages("remotes")
remotes::install_github("guido-s/netmeta",
ref = "develop", build_vignettes = TRUE)
```
## How to cite netmeta?
[Balduzzi S, Rücker G, Nikolakopoulou A, Papakonstantinou T, Salanti G, Efthimiou O, Schwarzer G (2023): netmeta: An R package for network meta-analysis using frequentist methods. *Journal of Statistical Software*, **106**, 1-40](https://doi.org/10.18637/jss.v106.i02)
A BibTeX entry for LaTeX users is provided by
```
citation(package = "netmeta")
```
### Bug Reports:
You can report bugs on GitHub under
[Issues](https://github.com/guido-s/netmeta/issues).
or using the R command
```r
bug.report(package = "netmeta")
```
(which is not supported in RStudio).
## References
[Balduzzi S, Rücker G, Nikolakopoulou A, Papakonstantinou T, Salanti G, Efthimiou O, Schwarzer G (2023): netmeta: An R package for network meta-analysis using frequentist methods. *Journal of Statistical Software*, **106**, 1-40](https://doi.org/10.18637/jss.v106.i02)
[Carlsen L, Bruggemann R (2014): Partial order methodology: a valuable tool in chemometrics. *Journal of Chemometrics*, **28**, 226-34](https://scholar.google.com/scholar?q=Partial+order+methodology%3A+a+valuable+tool+in+chemometrics)
[Chaimani A, Salanti G (2012): Using network meta-analysis to evaluate the existence of small-study effects in a network of interventions. *Research Synthesis Methods*, **3**, 161-76](https://scholar.google.com/scholar?q=Chaimani+Salanti+Using+network+meta-analysis+to+evaluate+the+existence+of+small-study+effects+in+a+network+of+interventions)
[Davies AL, Papakonstantinou T, Nikolakopoulou A, Rücker G, Galla T (2022): Network meta-analysis and random walks. *Statistics in Medicine*, **41**, 2091-2114](https://doi.org/10.1002/sim.9346)
[Dias S, Welton NJ, Caldwell DM, Ades AE (2010): Checking consistency in mixed treatment comparison meta-analysis. *Statistics in Medicine*, **29**, 932-44](https://scholar.google.com/scholar?q=Checking+consistency+in+mixed+treatment+comparison+meta-analysis)
[Efthimiou O, Rücker G, Schwarzer G, Higgins JPT, Egger M, Salanti G
(2019): Network meta-analysis of rare events using the Mantel-Haenszel method. *Statistics in Medicine*, **16**, 2992-3012](https://scholar.google.com/scholar?q=Efthimiou+Rücker+Schwarzer+Higgins+Egger+Salanti+2019+Mantel-Haenszel+model)
[Evrenoglou T, White IR, Afach S, Mavridis D, Chaimani A (2022): Network meta-analysis of rare events using penalized likelihood regression. *Statistics in Medicine*, **41**, 5203-19](https://doi.org/10.1002/sim.9562)).
[König J, Krahn U, Binder H (2013): Visualizing the flow of evidence in network meta-analysis and characterizing mixed treatment comparisons. *Statistics in Medicine*, **32**, 5414-29](https://scholar.google.com/scholar?q=König+Krahn+Binder+2013+Visualizing+the+flow+of+evidence+in+network+meta-analysis+and+characterizing+mixed+treatment+comparisons)
[Krahn U, Binder H, König J (2013): A graphical tool for locating inconsistency in network meta-analyses. *BMC Medical Research Methodology*, **13**, 35](https://doi.org/10.1186/1471-2288-13-35)
[Papakonstantinou T, Nikolakopoulou A, Rücker G, Chaimani A, Schwarzer G, Egger M, Salanti G (2018): Estimating the contribution of studies in network meta-analysis: paths, flows and streams. *F1000Research*, **7**, 610](https://doi.org/10.12688/f1000research.14770.3)
[Puhan MA, Schünemann HJ, Murad MH, Li T, Brignardello-Petersen R, Singh JA, Kessels AG, Guyatt GH, for the GRADE Working Group (2014): A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis. *BMJ*, **349**, g5630](https://scholar.google.com/scholar?q=puhan+schünemann+murad+2014+grade+network+meta-analysis))
[Rücker G (2012): Network meta-analysis, electrical networks and graph theory. *Research Synthesis Methods*, **3**, 312-24](https://scholar.google.com/scholar?q=Rücker+2012+Network+meta-analysis+electrical+networks+and+graph+theory)
[Rücker G, Schwarzer G (2014): Reduce dimension or reduce weights? Comparing two approaches to multi-arm studies in network meta-analysis. *Statistics in Medicine*, **33**, 4353-69](https://scholar.google.com/scholar?q=Rücker+Schwarzer+2014+Reduce+dimension+or+reduce+weights)
[Rücker G, Schwarzer G (2015): Ranking treatments in frequentist network meta-analysis works without resampling methods. *BMC Medical Research Methodology*, **15**, 58](https://doi.org/10.1186/s12874-015-0060-8)
[Rücker G, Schwarzer G (2016): Automated drawing of network plots in network meta-analysis. *Research Synthesis Methods*, **7**, 94-107](https://scholar.google.com/scholar?q=Rücker+Schwarzer+2016+Automated+drawing+of+network+plots+in+network+meta-analysis)
[Rücker G, Schwarzer G (2017): Resolve conflicting rankings of outcomes in network meta-analysis: Partial ordering of treatments. *Research Synthesis Methods*, **8**, 526-36](https://scholar.google.com/scholar?q=Rücker+Schwarzer+2017+resolve+conflicting+rankings+of+outcomes+in+network+meta-analysis)
[Rücker G, Petropoulou M, Schwarzer G (2020): Network meta-analysis of multicomponent interventions. *Biometrical Journal*, **62**, 808-21](https://doi.org/10.1002/bimj.201800167)
[Rücker G, Nikolakopoulou A, Papakonstantinou T, Salanti G, Riley RD, Schwarzer G (2020): The statistical importance of a study for a network meta-analysis estimate. *BMC Medical Research Methodology*, **20**, 190](https://doi.org/10.1186/s12874-020-01075-y)
[Salanti G, Ades AE, Ioannidis JPA (2011): Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. *Journal of Clinical Epidemiology*, **64**, 163-71](https://scholar.google.com/scholar?q=salanti+ades+ioannidis+2011+graphical+methods+multiple-treatment+meta-analysis)
[Schwarzer G, Carpenter JR and Rücker G (2015): *Meta-Analysis with R (Use R!)*. Springer International Publishing, Switzerland](https://link.springer.com/book/10.1007/978-3-319-21416-0)