A comprehensive set of functions providing frequentist methods for network meta-analysis (Balduzzi et al., 2023) <doi:10.18637/jss.v106.i02> and supporting Schwarzer et al. (2015) <doi:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis":
 - frequentist network meta-analysis following Rücker (2012) <doi:10.1002/jrsm.1058>;
 - additive network meta-analysis for combinations of treatments (Rücker et al., 2020) <doi:10.1002/bimj.201800167>;
 - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <doi:10.1002/sim.8158>, or penalised logistic regression (Evrenoglou et al., 2022) <doi:10.1002/sim.9562>;
 - rankograms and ranking of treatments by the Surface under the cumulative ranking curve (SUCRA) (Salanti et al., 2013) <doi:10.1016/j.jclinepi.2010.03.016>;
 - ranking of treatments using P-scores (frequentist analogue of SUCRAs without resampling) according to Rücker & Schwarzer (2015) <doi:10.1186/s12874-015-0060-8>;
 - split direct and indirect evidence to check consistency (Dias et al., 2010) <doi:10.1002/sim.3767>, (Efthimiou et al., 2019) <doi:10.1002/sim.8158>;
 - league table with network meta-analysis results;
 - 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012) <doi:10.1002/jrsm.57>;
 - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) <doi:10.1186/1471-2288-13-35>;
 - measures characterizing the flow of evidence between two treatments by König et al. (2013) <doi:10.1002/sim.6001>;
 - automated drawing of network graphs described in Rücker & Schwarzer (2016) <doi:10.1002/jrsm.1143>;
 - partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) <doi:10.1002/cem.2569>; (Rücker & Schwarzer, 2017) <doi:10.1002/jrsm.1270>;
 - contribution matrix as described in Papakonstantinou et al. (2018) <doi:10.12688/f1000research.14770.3> and Davies et al. (2022) <doi:10.1002/sim.9346>;
 - network meta-regression with a single continuous or binary covariate;
 - subgroup network meta-analysis.
| Version: | 3.2-0 | 
| Depends: | R (≥ 4.0.0), meta (≥ 8.0-1) | 
| Imports: | Matrix, metafor, MASS, mvtnorm, magic, igraph, ggplot2, colorspace, grid, dplyr, magrittr, methods | 
| Suggests: | Rgraphviz, graph, rgl, gridExtra, tictoc, writexl, R.rsp, cccp, brglm2, crossnma | 
| Published: | 2025-04-10 | 
| DOI: | 10.32614/CRAN.package.netmeta | 
| Author: | Gerta Rücker  [aut],
  Ulrike Krahn [aut],
  Jochem König  [aut],
  Orestis Efthimiou  [aut],
  Annabel Davies  [aut],
  Theodoros Papakonstantinou  [aut],
  Theodoros Evrenoglou  [ctb],
  Krzysztof Ciomek  [ctb] (Author of the original MIT-licensed R package hasseDiagram),
  Nana-Adjoa Kwarteng  [ctb],
  Guido Schwarzer  [aut, cre] | 
| Maintainer: | Guido Schwarzer  <guido.schwarzer at uniklinik-freiburg.de> | 
| License: | GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE] | 
| URL: | https://github.com/guido-s/netmeta | 
| NeedsCompilation: | no | 
| Citation: | netmeta citation info | 
| Materials: | NEWS | 
| In views: | ClinicalTrials, MetaAnalysis | 
| CRAN checks: | netmeta results |