netmeta: Network Meta-Analysis using Frequentist Methods

Official Git repository of R package netmeta

Description

A comprehensive set of functions providing frequentist methods for network meta-analysis:

• frequentist network meta-analysis (Rücker, 2012; Rücker & Schwarzer, 2014);

• net heat plot and design-based decomposition of Cochran's Q (Krahn et al., 2013);

• measures characterizing the flow of evidence between two treatments (König et al., 2013);

• ranking of treatments based on frequentist analogue of SUCRA (Rücker & Schwarzer, 2015);

• partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014; Rücker & Schwarzer, 2017);

• split direct and indirect evidence to check consistency (Dias et al., 2010);

• league table with network meta-analysis results;

• additive network meta-analysis for combinations of treatments (Rücker et al., 2019);

• network meta-analysis of binary data using the Mantel-Haenszel method or the non-central hypergeometric distribution (Efthimiou et al., 2019);

• 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012);

• automated drawing of network graphs (Rücker & Schwarzer, 2016).

Furthermore, R package netmeta provides functions and datasets to support Schwarzer et al. (2015), Chapter 8 "Network Meta-Analysis", http://meta-analysis-with-r.org/ .

References

Carlsen L, Bruggemann R (2014): Partial order methodology: a valuable tool in chemometrics. Journal of Chemometrics, 28, 226-34

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

Dias S, Welton NJ, Caldwell DM, Ades AE (2010): Checking consistency in mixed treatment comparison meta-analysis. Statistics in Medicine, 29, 932-44

Efthimiou O, Rücker G, Schwarzer G, Higgins J, Egger M, Salanti G (2019): A Mantel-Haenszel model for network meta-analysis of rare events. Statistics in Medicine, 1-21

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

Krahn U, Binder H, König J (2013): A graphical tool for locating inconsistency in network meta-analyses. BMC Medical Research Methodology, 13, 35

Rücker G (2012): Network meta-analysis, electrical networks and graph theory. Research Synthesis Methods, 3, 312-24

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

Rücker G, Schwarzer G (2015): Ranking treatments in frequentist network meta-analysis works without resampling methods. BMC Medical Research Methodology, 15, 58

Rücker G, Schwarzer G (2016): Automated drawing of network plots in network meta-analysis. Research Synthesis Methods, 7, 94-107

Rücker G, Schwarzer G (2017): Resolve conflicting rankings of outcomes in network meta-analysis: Partial ordering of treatments. Research Synthesis Methods, 8, 526-36

Rücker G, Petropoulou M, Schwarzer G (2019): Network meta-analysis of multicomponent interventions. Biometrical Journal, 1-14

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

Installation

Current official release:

install.packages("netmeta")

Current development version on GitHub:

Installation using R package devtools:

install.packages("devtools")
devtools::install_github("guido-s/netmeta", ref = "develop")

Note, the development version of netmeta always has version number 6.6-6.

Bug Reports:

bug.report(package = "netmeta")

The bug.report function is not supported in RStudio. Please send an email to Guido Schwarzer sc@imbi.uni-freiburg.de if you use RStudio.

You can also report bugs on GitHub under Issues.