{ "_id": "6a1ed4b3b401979e7340e2e6", "Package": "mvnma", "Title": "Multivariate Network Meta-Analysis using Bayesian Methods", "Version": "0.1-0", "Date": "2026-05-15", "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\")))", "Maintainer": "Theodoros Evrenoglou\n", "URL": "https://github.com/TEvrenoglou/mvnma", "Description": "Tools to conduct Bayesian multivariate network\nmeta-analysis providing - the single correlation coefficient\nmodel by Efthimiou et al. (2015)\n; - per-outcome treatment\nhierarchies using the surface under the cumulative ranking\ncurve (SUCRA), the probability of best value, or median (or\nmean) ranks (Salanti et al., 2011)\n; - across-outcomes\nbenefit-risk assessment using the VišeKriterijumska\nOptimizacija I Kompromisno Rešenje (VIKOR) method (Opricovic &\nTzeng, 2004) ; - convergence\nchecks using trace plots, density plots, or the R-hat\nstatistic; - forest plots of treatment estimates, scatter plots\nof per-outcome rankings, Hasse diagrams (Carlsen & Bruggemann,\n2014) to visualize the partial order of\nthe treatments across all outcomes.", "License": "GPL (>= 2)", "Encoding": "UTF-8", "NeedsCompilation": "no", "Config/roxygen2/version": "8.0.0", "Config/pak/sysreqs": "cmake libglpk-dev make jags libicu-dev libxml2-dev\nlibx11-dev", "Repository": "https://tevrenoglou.r-universe.dev", "Date/Publication": "2026-05-15 11:53:28 UTC", "RemoteUrl": "https://github.com/tevrenoglou/mvnma", "RemoteRef": "HEAD", 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