{ "_id": "6a35a9243efcd9bda43ef975", "Package": "crossnma", "Title": "Cross-Design & Cross-Format Network Meta-Analysis and Regression", "Version": "1.3.1", "Date": "2026-06-19", "Authors@R": "c(\nperson(\"Tasnim\", \"Hamza\",\nemail = \"hamza.a.tasnim@gmail.com\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-4700-6990\")),\nperson(\"Guido\", \"Schwarzer\",\nemail = \"guido.schwarzer@uniklinik-freiburg.de\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-6214-9087\")),\nperson(\"Georgia\", \"Salanti\",\nemail = \"georgia.salanti@ispm.unibe.ch\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-3830-8508\")))", "Author": "Tasnim Hamza [aut] (ORCID:\n), Guido Schwarzer [aut,\ncre] (ORCID: ), Georgia\nSalanti [aut] (ORCID: )", "Maintainer": "Guido Schwarzer ", "URL": "https://github.com/guido-s/crossnma", "Description": "Network meta-analysis and meta-regression (allows\nincluding up to three covariates) for individual participant\ndata, aggregate data, and mixtures of both formats using the\nthree-level hierarchical model. Each format can come from\nrandomized controlled trials or non-randomized studies or\nmixtures of both. Estimates are generated in a Bayesian\nframework using JAGS. The implemented models are described by\nHamza et al. 2023 .", "License": "GPL (>= 2)", "Encoding": "UTF-8", "LazyData": "true", "VignetteBuilder": "knitr", "Config/roxygen2/version": "8.0.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-19 20:36:35 UTC", "User": "root" }, "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-06-19 20:08:18 UTC", "RemoteUrl": "https://github.com/cran/crossnma", "RemoteRef": "HEAD", "RemoteSha": "d4629b3aae25d79aead85cb2bd7c79f8e2dc32c7", "MD5sum": "5bc4a835dc67e0eaac08b50768518aa3", "_user": "cran", "_type": "src", "_file": "crossnma_1.3.1.tar.gz", "_fileid": "e4584065efd0253b70de83735db7b0bde59a2d1caacca7fab0511404973ce31f", "_filesize": 1240425, "_sha256": "e4584065efd0253b70de83735db7b0bde59a2d1caacca7fab0511404973ce31f", "_created": "2026-06-19T20:36:35.000Z", "_published": "2026-06-19T20:40:04.214Z", "_distro": "noble", "_jobs": [ { "job": 82419230732, "time": 155, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "WARNING", "artifact": "7758014409" }, { "job": 82419230712, "time": 162, "config": "linux-release-x86_64", "r": "4.6.0", "check": "WARNING", "artifact": "7758015825" }, { "job": 82418575820, "time": 328, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7757977249" }, { "job": 82419230719, "time": 132, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7758008911" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/27847121200", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/crossnma", "_commit": { "id": "d4629b3aae25d79aead85cb2bd7c79f8e2dc32c7", "author": "Guido Schwarzer ", "committer": "cran-robot ", "message": "version 1.3.1\n", "time": 1781899698 }, "_maintainer": { "name": "Guido Schwarzer", "email": "guido.schwarzer@uniklinik-freiburg.de", "login": "guido-s", "description": "Research interests: meta-analysis, statistical programming - Author of Use-R! book \"Meta-Analysis with R\" (http://www.springer.com/gp/book/9783319214153)", "uuid": 10942806, "orcid": "0000-0001-6214-9087" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.0.0", "role": "Depends" }, { "package": "meta", "version": ">= 8.5-0", "role": "Depends" }, { "package": "netmeta", "version": ">= 3.5-0", "role": "Depends" }, { "package": "rjags", "role": "Imports" }, { "package": "coda", "role": "Imports" }, { "package": "dplyr", "role": "Imports" }, { "package": "plyr", "role": "Imports" }, { "package": "rlang", "role": "Imports" }, { "package": "magrittr", "role": "Imports" }, { "package": "tidyr", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [ { "week": "2026-25", "n": 1 } ], "_tags": [ { "name": "1.3.1", "date": "2026-06-19" } ], "_stars": 0, "_contributors": [ { "user": "guido-s", "count": 5, "uuid": 10942806 } ], "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "followers": 610, "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 3725, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/crossnma" }, "_devurl": "https://github.com/guido-s/crossnma", "_searchresults": 13, "_topics": [ "jags", "cpp" ], "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/crossnma.html", "extra/NEWS.html", "extra/NEWS.txt", "manual.pdf" ], "_homeurl": "https://github.com/htx-r/crossnma", "_realowner": "htx-r", "_cranurl": false, "_releases": [ { "version": "1.0.1", "date": "2022-04-15" }, { "version": "1.1.0", "date": "2023-05-08" }, { "version": "1.2.0", "date": "2023-09-18" }, { "version": "1.3.0", "date": "2024-11-28" }, { "version": "1.3.1", "date": "2026-06-19" } ], "_exports": [ "crossnma", "crossnma.model", "league" ], "_datasets": [ { "name": "ipddata", "title": "Simulated individual participant dataset.", "object": "ipddata", "class": [ "data.frame" ], "fields": [ "id", "relapse", "treat", "design", "age", "sex", "rob", "unfavored", "bias.group", "year" ], "rows": 1944, "table": true, "tojson": true }, { "name": "stddata", "title": "Simulated aggregate dataset.", "object": "stddata", "class": [ "data.frame" ], "fields": [ "id", "n", "relapse", "treat", "design", "age", "sex", "rob", "unfavored", "bias.group", "year" ], "rows": 4, "table": true, "tojson": true } ], "_help": [ { "page": "crossnma-package", "title": "crossnma: An R package for synthesizing cross-design evidence and cross-format data using Bayesian methods in network meta-analysis and network meta-regression", "topics": [ "crossnma-package" ] }, { "page": "crossnma", "title": "Run JAGS to fit cross NMA and NMR", "topics": [ "crossnma" ] }, { "page": "crossnma.model", "title": "Create JAGS model and data to perform cross network meta analysis or meta-regression", "topics": [ "crossnma.model" ] }, { "page": "heatplot.crossnma", "title": "Heat Plot", "topics": [ "heatplot.crossnma" ] }, { "page": "ipddata", "title": "Simulated individual participant dataset.", "topics": [ "ipddata" ] }, { "page": "league.crossnma", "title": "League Table", "topics": [ "league", "league.crossnma", "print.league.crossnma" ] }, { "page": "netconnection.crossnma", "title": "Get information on network connectivity (number of subnetworks, distance matrix)", "topics": [ "netconnection.crossnma" ] }, { "page": "netconnection.crossnma.model", "title": "Get information on network connectivity (number of subnetworks, distance matrix)", "topics": [ "netconnection.crossnma.model" ] }, { "page": "netgraph.crossnma", "title": "Produce a network plot", "topics": [ "netgraph.crossnma" ] }, { "page": "netgraph.crossnma.model", "title": "Produce a network plot", "topics": [ "netgraph.crossnma.model" ] }, { "page": "plot.crossnma", "title": "Trace plot of MCMC output", "topics": [ "plot.crossnma" ] }, { "page": "print.crossnma", "title": "Print results of cross-design & -format network meta-analysis or regression", "topics": [ "print.crossnma" ] }, { "page": "print.crossnma.model", "title": "Print call used to create JAGS model for cross-design & -format network meta-analysis or regression", "topics": [ "print.crossnma.model" ] }, { "page": "print.summary.crossnma", "title": "Print summary of cross-design & -format network meta-analysis or regression", "topics": [ "print.summary.crossnma" ] }, { "page": "print.summary.crossnma.model", "title": "Print code of JAGS model for cross-design & -format network meta-analysis or regression", "topics": [ "print.summary.crossnma.model" ] }, { "page": "stddata", "title": "Simulated aggregate dataset.", "topics": [ "stddata" ] }, { "page": "summary.crossnma", "title": "Summary function for crossnma object", "topics": [ "summary.crossnma" ] }, { "page": "summary.crossnma.model", "title": "Summary function for crossnma.model object", "topics": [ "summary.crossnma.model" ] } ], "_rundeps": [ "abind", "bit", "bit64", "boot", "cli", "clipr", "coda", "colorspace", "CompQuadForm", "cpp11", "crayon", "digest", "dplyr", "farver", "generics", "ggplot2", "ggrepel", "glue", "gtable", "hms", "igraph", "isoband", "labeling", "lattice", "lifecycle", "lme4", "magic", "magrittr", "MASS", "mathjaxr", "Matrix", "meta", "metabook", "metadat", "metafor", "minqa", "mvtnorm", "netmeta", "nlme", "nloptr", "numDeriv", "pbapply", "pillar", "pkgconfig", "plyr", "prettyunits", "progress", "purrr", "R6", "rbibutils", "RColorBrewer", "Rcpp", "RcppEigen", "Rdpack", "readr", "reformulas", "rjags", "rlang", "S7", "scales", "stringi", "stringr", "tibble", "tidyr", "tidyselect", "tzdb", "utf8", "vctrs", "viridisLite", "vroom", "withr", "xml2" ], "_sysdeps": [ { "shlib": "libjags", "package": "jags", "headers": "jags", "source": "jags", "version": "4.3.2-2.2404.0", "name": "jags", "homepage": "https://mcmc-jags.sourceforge.io", "description": "Just Another Gibbs Sampler for Bayesian MCMC - binary" }, { "shlib": "libstdc++", "package": "libstdc++6", "source": "gcc", "version": "14.2.0-4ubuntu2~24.04.1", "name": "c++", "homepage": "http://gcc.gnu.org/", "description": "GNU Standard C++ Library v3" } ], "_vignettes": [ { "source": "crossnma.Rmd", "filename": "crossnma.html", "title": "crossnma: Cross-Design & Cross-Format Network Meta-Analysis and Regression", "author": "Tasnim Hamza, Guido Schwarzer and Georgia Salanti", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "The synthesis models", "Unadjusted network meta-regression (NMR)", "Using non-randomized studies (NRS) to construct priors for the treatment effects", "Bias-adjusted model 1", "Bias-adjusted model 2", "Assumptions about the model parameters", "Synthesis of studies comparing drugs for relapsing-remitting multiple sclerosis", "Description of the data", "Analysis", "Unadjusted network meta-analysis", "Unadjusted network meta-regression", "References" ], "created": "2022-04-15 09:02:29", "modified": "2026-06-19 20:08:18", "commits": 4 } ], "_score": 2.6850696293911485, "_indexed": false, "_nocasepkg": "crossnma", "_universes": [ "cran" ], "_indexurl": "https://htx-r.r-universe.dev/crossnma", "_previous": "1.3.0", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.3.1", "date": "2026-06-19T20:38:47.000Z", "distro": "noble", "commit": "d4629b3aae25d79aead85cb2bd7c79f8e2dc32c7", "fileid": "f09cdd9aa1e01f5c5011f4f4684a16588414635dd53b57924856421130af5f25", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/cran/actions/runs/27847121200" }, { "r": "4.6.0", "os": "linux", "version": "1.3.1", "date": "2026-06-19T20:38:55.000Z", "distro": "noble", "commit": "d4629b3aae25d79aead85cb2bd7c79f8e2dc32c7", "fileid": "bfa87ead36a1316a05f106fec3403b2428e521b72e0e6439b1dfd502bb2448b6", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/cran/actions/runs/27847121200" }, { "r": "4.6.0", "os": "wasm", "version": "1.3.1", "date": "2026-06-19T20:39:17.000Z", "commit": "d4629b3aae25d79aead85cb2bd7c79f8e2dc32c7", "fileid": "25f5aa8959333330c83e043276ab75de27c6e43c6923a0b1051be1ca4c6950ab", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/27847121200" } ] }