netmeta-package

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netmeta: Brief overview of methods and general hints

R package netmeta provides frequentist methods for network meta-analysis and supports Schwarzer et al. (2015), Chapter 8 on network meta-analysis http://meta-analysis-with-r.org/.

Details

R package netmeta is an add-on package for meta providing the following meta-analysis methods:

  • frequentist network meta-analysis (function netmeta) based on R<U+00FC>cker (2012);

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

  • measures characterizing the flow of evidence between two treatments (netmeasures) described in K<U+00F6>nig et al. (2013);

  • ranking of treatments (netrank) based on frequentist analogue of SUCRA (R<U+00FC>cker & Schwarzer, 2015);

  • partial order of treatment rankings (netposet, plot.netposet) and Hasse diagram (hasse) according to Carlsen & Bruggemann (2014);

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

  • league table with network meta-analysis results (netleague);

  • automated drawing of network graphs (netgraph) described in R<U+00FC>cker & Schwarzer (2016).

Furthermore, functions and datasets from netmeta are utilised in Schwarzer et al. (2015), Chapter 8 "Network Meta-Analysis", http://meta-analysis-with-r.org/.

Type help(package = "netmeta") for a listing of R functions available in netmeta.

Type citation("netmeta") on how to cite netmeta in publications.

To report problems and bugs

  • type bug.report(package = "netmeta") if you do not use RStudio,

  • send an email to Guido Schwarzer sc@imbi.uni-freiburg.de if you use RStudio.

The development version of netmeta is available on GitHub https://github.com/guido-s/netmeta.

References

Carlsen L, Bruggemann R (2014), Partial order methodology: a valuable tool in chemometrics. Journal of Chemometrics, 28, 226--34, DOI:10.1002/cem.2569 .

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

K<U+00F6>nig J, Krahn U, Binder H (2013). Visualizing the flow of evidence in network meta-analysis and characterizing mixed treatment comparisons. Statistics in Medicine, 32(30), 5414--29.

Krahn U, Binder H, K<U+00F6>nig J (2013), A graphical tool for locating inconsistency in network meta-analyses. BMC Medical Research Methodology, 13, 35.

R<U+00FC>cker G (2012), Network meta-analysis, electrical networks and graph theory. Research Synthesis Methods, 3, 312--24.

R<U+00FC>cker G & Schwarzer G (2015), Ranking treatments in frequentist network meta-analysis works without resampling methods. BMC Medical Research Methodology, 15, 58, DOI:10.1186/s12874-015-0060-8 .

R<U+00FC>cker G & Schwarzer G (2016), Automated drawing of network plots in network meta-analysis. Research Synthesis Methods, 7, 94--107.

Schwarzer G, Carpenter JR and R<U+00FC>cker G (2015), Meta-Analysis with R (Use-R!). Springer International Publishing, Switzerland. http://www.springer.com/gp/book/9783319214153

Aliases
  • netmeta-package
Documentation reproduced from package netmeta, version 0.9-5, License: GPL (>= 2)

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