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  "Title": "Multivariate Network Meta-Analysis using Bayesian Methods",
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  "Date": "2026-09-18",
  "Authors@R": "c(person(\"Theodoros\", \"Evrenoglou\",\nrole = c(\"aut\", \"cre\"),\nemail = \"theodoros.evrenoglou@uniklinik-freiburg.de\",\ncomment = c(ORCID = \"0000-0003-3336-8058\")),\nperson(\"Guido\", \"Schwarzer\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0001-6214-9087\")))",
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  "Description": "Tools to conduct Bayesian multivariate network\nmeta-analysis providing - the single correlation coefficient\nmodel by Efthimiou et al. (2015)\n<doi:10.1093/biostatistics/kxu030>; - per-outcome consistency\nchecks using the node-splitting method (Dias et al., 2010)\n<doi:10.1002/sim.3767>; - per-outcome treatment hierarchies\nusing the surface under the cumulative ranking curve (SUCRA),\nthe probability of best value, or median (or mean) ranks\n(Salanti et al., 2011) <doi:10.1016/j.jclinepi.2010.03.016>; -\nacross-outcomes benefit-risk assessment using the\nVišeKriterijumska Optimizacija I Kompromisno Rešenje (VIKOR)\nmethod (Opricovic & Tzeng, 2004)\n<doi:10.1016/S0377-2217(03)00020-1>; - convergence checks using\ntrace plots, density plots, or the R-hat statistic; - forest\nplots of treatment estimates and consistency checks, scatter\nplots of per-outcome rankings, Hasse diagrams (Carlsen &\nBruggemann, 2014) <doi:10.1002/cem.2569> to visualize the\npartial order of the treatments across all outcomes.",
  "License": "GPL (>= 2)",
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