netmeta

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; - 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.