{ "_id": "6a1d36601d7bb097a0a3d123", "Type": "Package", "Package": "rnmamod", "Title": "Bayesian Network Meta-Analysis with Missing Participants", "Version": "0.5.0", "Date": "2025-06-13", "Authors@R": "c(\nperson(\"Loukia\", \"Spineli\", email = \"Spineli.Loukia@mh-hannover.de\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Chrysostomos\", \"Kalyvas\", role = \"ctb\"),\nperson(\"Katerina\", \"Papadimitropoulou\", role = \"ctb\")\n)", "Maintainer": "Loukia Spineli ", "Description": "A comprehensive suite of functions to perform and\nvisualise pairwise and network meta-analysis with aggregate\nbinary or continuous missing participant outcome data. The\npackage covers core Bayesian one-stage models implemented in a\nsystematic review with multiple interventions, including\nfixed-effect and random-effects network meta-analysis,\nmeta-regression, evaluation of the consistency assumption via\nthe node-splitting approach and the unrelated mean effects\nmodel (original and revised model proposed by Spineli, (2021)\n), and sensitivity analysis (see\nSpineli et al., (2021) and Spineli et\nal., (2021) ). Missing\nparticipant outcome data are addressed in all models of the\npackage (see Spineli, (2019) ,\nSpineli et al., (2019) , Spineli, (2019)\n, and Spineli et al.,\n(2021) ). The robustness to\nprimary analysis results can also be investigated using a novel\nintuitive index (see Spineli et al., (2021)\n and Spineli et al., (2021)\n). Methods to evaluate the\ntransitivity assumption using trial dissimilarities and\nhierarchical clustering are provided (see Spineli, (2024)\n, and Spineli et al., (2025)\n). A novel index to facilitate\ninterpretation of local inconsistency is also available (see\nSpineli, (2024) ) The package\nalso offers a rich, user-friendly visualisation toolkit that\naids in appraising and interpreting the results thoroughly and\npreparing the manuscript for journal submission. The\nvisualisation tools comprise the network plot, forest plots,\npanel of diagnostic plots, heatmaps on the extent of missing\nparticipant outcome data in the network, league heatmaps on\nestimation and prediction, rankograms, Bland-Altman plot,\nleverage plot, deviance scatterplot, heatmap of robustness,\nbarplot of Kullback-Leibler divergence, heatmap of comparison\ndissimilarities and dendrogram of comparison clustering. The\npackage also allows the user to export the results to an Excel\nfile at the working directory.", "License": "GPL (>= 3)", "URL": "https://CRAN.R-project.org/package=rnmamod,\nhttps://github.com/LoukiaSpin/rnmamod,\nhttps://loukiaspin.github.io/rnmamod/", "BugReports": "https://github.com/LoukiaSpin/rnmamod/issues", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Encoding": "UTF-8", "Language": "en-US", "LazyData": "true", "RoxygenNote": "7.3.2", "Config/pak/sysreqs": "cmake libglpk-dev make libmagick++-dev gsfonts jags\nlibicu-dev libjpeg-dev libpng-dev libuv1-dev libxml2-dev\nlibssl-dev libx11-dev zlib1g-dev", "Repository": "https://loukiaspin.r-universe.dev", "Date/Publication": "2026-01-30 15:41:01 UTC", "RemoteUrl": "https://github.com/loukiaspin/rnmamod", "RemoteRef": "HEAD", "RemoteSha": "9c70b332c812f635080ca2444bb77cfa939fde07", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-01 07:20:01 UTC", "User": "root" }, "Author": "Loukia Spineli [aut, 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