{
  "_id": "6a12a439acfb0bcc41d12a80",
  "Package": "NCC",
  "Title": "Simulation and Analysis of Platform Trials with Non-Concurrent\nControls",
  "Version": "1.0",
  "Author": "Pavla Krotka [aut, cre]\n(<https://orcid.org/0000-0001-5727-4270>), Marta Bofill Roig\n[aut, ths] (<https://orcid.org/0000-0002-4400-7541>), Katharina\nHees [aut], Peter Jacko [aut], Dominic Magirr [aut], Martin\nPosch [ctb] (<https://orcid.org/0000-0001-8499-8573>)",
  "Maintainer": "Pavla Krotka <pavla.krotka@upc.edu>",
  "Authors@R": "c(person(given = \"Pavla\",\nfamily = \"Krotka\",\nrole = c(\"aut\", \"cre\"),\nemail = \"pavla.krotka@upc.edu\",\ncomment = c(ORCID = \"0000-0001-5727-4270\")),\nperson(\"Marta\", \"Bofill Roig\", email = \"marta.bofill.roig@upc.edu\", role = c(\"aut\", \"ths\"), comment = c(ORCID = \"0000-0002-4400-7541\")),\nperson(\"Katharina\", \"Hees\", email = \"Katharina.Hees@pei.de\", role = c(\"aut\")),\nperson(\"Peter\", \"Jacko\", email = \"peter@berryconsultants.net\", role = c(\"aut\")),\nperson(\"Dominic\", \"Magirr\", email = \"dominic.magirr@novartis.com\", role = c(\"aut\")),\nperson(\"Martin\", \"Posch\", email = \"martin.posch@meduniwien.ac.at\", role = c(\"ctb\"), comment = c(ORCID = \"0000-0001-8499-8573\")))",
  "Description": "Design and analysis of flexible platform trials with\nnon-concurrent controls. Functions for data generation,\nanalysis, visualization and running simulation studies are\nprovided. The implemented analysis methods are described in:\nBofill Roig et al. (2022) <doi:10.1186/s12874-022-01683-w>,\nSaville et al. (2022) <doi:10.1177/17407745221112013> and\nSchmidli et al. (2014) <doi:10.1111/biom.12242>.",
  "URL": "https://pavlakrotka.github.io/NCC/,\nhttps://github.com/pavlakrotka/NCC",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "SystemRequirements": "JAGS 4.x.y",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.3.2",
  "VignetteBuilder": "knitr",
  "BugReports": "https://github.com/pavlakrotka/NCC/issues",
  "Config/pak/sysreqs": "cmake libgmp3-dev make libgsl0-dev jags libicu-dev",
  "Repository": "https://pavlakrotka.r-universe.dev",
  "Date/Publication": "2025-03-10 14:29:16 UTC",
  "RemoteUrl": "https://github.com/pavlakrotka/ncc",
  "RemoteRef": "HEAD",
  "RemoteSha": "f439de7b785d13669add0ba53666c96bd4d0b95f",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-24 06:55:59 UTC",
    "User": "root"
  },
  "MD5sum": "7710c1d9d24e5ec8ce4f5a427050554f",
  "_user": "pavlakrotka",
  "_type": "src",
  "_file": "NCC_1.0.tar.gz",
  "_fileid": "66b74aa09daa33047de9236e261c543cd8fbe403568776796cee30fc703f2879",
  "_filesize": 1173728,
  "_sha256": "66b74aa09daa33047de9236e261c543cd8fbe403568776796cee30fc703f2879",
  "_created": "2026-05-24T06:55:59.000Z",
  "_published": "2026-05-24T07:09:45.106Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 77578736776,
      "time": 278,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7183072874"
    },
    {
      "job": 77578736777,
      "time": 272,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7183072277"
    },
    {
      "job": 77578736770,
      "time": 170,
      "config": "macos-oldrel-arm64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7183125281"
    },
    {
      "job": 77578736773,
      "time": 191,
      "config": "macos-release-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7183128455"
    },
    {
      "job": 77578481815,
      "time": 304,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7183044873"
    },
    {
      "job": 77578736771,
      "time": 145,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7183058446"
    },
    {
      "job": 77578736787,
      "time": 231,
      "config": "windows-devel",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7183067383"
    },
    {
      "job": 77578736778,
      "time": 229,
      "config": "windows-oldrel",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7183067242"
    },
    {
      "job": 77578736779,
      "time": 220,
      "config": "windows-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7183066210"
    }
  ],
  "_buildurl": "https://github.com/r-universe/pavlakrotka/actions/runs/26354439911",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/pavlakrotka/ncc",
  "_commit": {
    "id": "f439de7b785d13669add0ba53666c96bd4d0b95f",
    "author": "Pavla Krotka <pavla.krotka@gmail.com>",
    "committer": "Pavla Krotka <pavla.krotka@gmail.com>",
    "message": "clean dependencies\n",
    "time": 1741616956
  },
  "_maintainer": {
    "name": "Pavla Krotka",
    "email": "pavla.krotka@upc.edu",
    "login": "pavlakrotka",
    "description": "",
    "uuid": 77578027,
    "orcid": "0000-0001-5727-4270"
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "rlang",
      "role": "Imports"
    },
    {
      "package": "stats",
      "role": "Imports"
    },
    {
      "package": "RBesT",
      "role": "Imports"
    },
    {
      "package": "rjags",
      "role": "Imports"
    },
    {
      "package": "ggplot2",
      "role": "Imports"
    },
    {
      "package": "lmerTest",
      "role": "Imports"
    },
    {
      "package": "parallelly",
      "role": "Imports"
    },
    {
      "package": "foreach",
      "role": "Imports"
    },
    {
      "package": "iterators",
      "role": "Imports"
    },
    {
      "package": "spaMM",
      "role": "Imports"
    },
    {
      "package": "mgcv",
      "role": "Imports"
    },
    {
      "package": "splines",
      "role": "Imports"
    },
    {
      "package": "BayesPPD",
      "role": "Imports"
    },
    {
      "package": "doFuture",
      "role": "Imports"
    },
    {
      "package": "future",
      "role": "Imports"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    }
  ],
  "_owner": "pavlakrotka",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_topics": [
    "clinical-trials",
    "platform-trials",
    "simulation",
    "statistical-inference",
    "jags",
    "cpp"
  ],
  "_stars": 5,
  "_contributors": [
    {
      "user": "pavlakrotka",
      "count": 259,
      "uuid": 77578027
    },
    {
      "user": "martabofillroig",
      "count": 24,
      "uuid": 26740298
    },
    {
      "user": "khees",
      "count": 3,
      "uuid": 21100276
    }
  ],
  "_userbio": {
    "uuid": 77578027,
    "type": "user",
    "name": "Pavla Krotka"
  },
  "_downloads": {
    "count": 257,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/NCC"
  },
  "_devurl": "https://github.com/pavlakrotka/ncc",
  "_pkgdown": "https://pavlakrotka.github.io/NCC/",
  "_searchresults": 30,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NCC.html",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/pavlakrotka/ncc",
  "_realowner": "pavlakrotka",
  "_cranurl": true,
  "_releases": [
    {
      "version": "1.0",
      "date": "2023-03-03"
    }
  ],
  "_exports": [
    "all_models",
    "datasim_bin",
    "datasim_bin_2",
    "datasim_cont",
    "fixmodel_bin",
    "fixmodel_cal_bin",
    "fixmodel_cal_cont",
    "fixmodel_cont",
    "fixmodel_lin_cont",
    "gam_cont",
    "get_ss_matrix",
    "inv_u_trend",
    "linear_trend",
    "MAPprior_bin",
    "MAPprior_cont",
    "MAPpriorNew_cont",
    "mixmodel_AR1_cal_cont",
    "mixmodel_AR1_cont",
    "mixmodel_cal_cont",
    "mixmodel_cont",
    "mixmodel_int_cal_cont",
    "mixmodel_int_cont",
    "piecewise_cal_cont",
    "piecewise_cont",
    "plot_trial",
    "poolmodel_bin",
    "poolmodel_cont",
    "powerprior_cont",
    "seasonal_trend",
    "sepmodel_adj_bin",
    "sepmodel_adj_cont",
    "sepmodel_bin",
    "sepmodel_cont",
    "sim_study",
    "sim_study_par",
    "splines_cal_cont",
    "splines_cont",
    "sw_trend",
    "timemachine_bin",
    "timemachine_cont"
  ],
  "_help": [
    {
      "page": "datasim_bin",
      "title": "Simulate binary data from a platform trial with a shared control arm and a given number of experimental treatment arms entering at given time points",
      "topics": [
        "datasim_bin"
      ]
    },
    {
      "page": "datasim_bin_2",
      "title": "Simulate binary data from a platform trial with a shared control arm and a given number of experimental treatment arms entering at given time points using a user-specified sample size matrix",
      "topics": [
        "datasim_bin_2"
      ]
    },
    {
      "page": "datasim_cont",
      "title": "Simulate continuous data from a platform trial with a shared control arm and a given number of experimental treatment arms entering at given time points",
      "topics": [
        "datasim_cont"
      ]
    },
    {
      "page": "fixmodel_bin",
      "title": "Frequentist logistic regression model analysis for binary data adjusting for periods",
      "topics": [
        "fixmodel_bin"
      ]
    },
    {
      "page": "fixmodel_cal_bin",
      "title": "Frequentist logistic regression model analysis for binary data adjusting for calendar time units",
      "topics": [
        "fixmodel_cal_bin"
      ]
    },
    {
      "page": "fixmodel_cal_cont",
      "title": "Frequentist linear regression model analysis for continuous data adjusting for calendar time units",
      "topics": [
        "fixmodel_cal_cont"
      ]
    },
    {
      "page": "fixmodel_cont",
      "title": "Frequentist linear regression model analysis for continuous data adjusting for periods",
      "topics": [
        "fixmodel_cont"
      ]
    },
    {
      "page": "fixmodel_lin_cont",
      "title": "Frequentist linear regression model analysis for continuous data with linear adjustment for time",
      "topics": [
        "fixmodel_lin_cont"
      ]
    },
    {
      "page": "gam_cont",
      "title": "Generalized additive model analysis for continuous data",
      "topics": [
        "gam_cont"
      ]
    },
    {
      "page": "get_ss_matrix",
      "title": "Sample size matrix for a platform trial with a given number of treatment arms",
      "topics": [
        "get_ss_matrix"
      ]
    },
    {
      "page": "inv_u_trend",
      "title": "Generation of an inverted-u trend",
      "topics": [
        "inv_u_trend"
      ]
    },
    {
      "page": "linear_trend",
      "title": "Generation of a linear trend that starts in a given period",
      "topics": [
        "linear_trend"
      ]
    },
    {
      "page": "MAPprior_bin",
      "title": "Analysis for binary data using the MAP Prior approach",
      "topics": [
        "MAPprior_bin"
      ]
    },
    {
      "page": "MAPprior_cont",
      "title": "Analysis for continuous data using the MAP Prior approach",
      "topics": [
        "MAPprior_cont"
      ]
    },
    {
      "page": "MAPpriorNew_cont",
      "title": "Analysis for continuous data using the MAP Prior approach",
      "topics": [
        "MAPpriorNew_cont"
      ]
    },
    {
      "page": "mixmodel_AR1_cal_cont",
      "title": "Mixed regression model analysis for continuous data adjusting for calendar time units as a random factor with AR1 correlation structure",
      "topics": [
        "mixmodel_AR1_cal_cont"
      ]
    },
    {
      "page": "mixmodel_AR1_cont",
      "title": "Mixed regression model analysis for continuous data adjusting for periods as a random factor with AR1 correlation structure",
      "topics": [
        "mixmodel_AR1_cont"
      ]
    },
    {
      "page": "mixmodel_cal_cont",
      "title": "Mixed regression model analysis for continuous data adjusting for calendar time units as a random factor",
      "topics": [
        "mixmodel_cal_cont"
      ]
    },
    {
      "page": "mixmodel_cont",
      "title": "Mixed regression model analysis for continuous data adjusting for periods as a random factor",
      "topics": [
        "mixmodel_cont"
      ]
    },
    {
      "page": "mixmodel_int_cal_cont",
      "title": "Mixed regression model analysis for continuous data using the covariates treatment and calendar time unit as fixed effects and the interaction between them as a random effect",
      "topics": [
        "mixmodel_int_cal_cont"
      ]
    },
    {
      "page": "mixmodel_int_cont",
      "title": "Mixed regression model analysis for continuous data using the covariates treatment and period as fixed effects and the interaction between them as a random effect",
      "topics": [
        "mixmodel_int_cont"
      ]
    },
    {
      "page": "piecewise_cal_cont",
      "title": "Model-based analysis for continuous data using discontinuous piecewise polynomials per calendar time unit",
      "topics": [
        "piecewise_cal_cont"
      ]
    },
    {
      "page": "piecewise_cont",
      "title": "Model-based analysis for continuous data using discontinuous piecewise polynomials per period",
      "topics": [
        "piecewise_cont"
      ]
    },
    {
      "page": "plot_trial",
      "title": "Function for visualizing the simulated trial",
      "topics": [
        "plot_trial"
      ]
    },
    {
      "page": "poolmodel_bin",
      "title": "Pooled analysis for binary data",
      "topics": [
        "poolmodel_bin"
      ]
    },
    {
      "page": "poolmodel_cont",
      "title": "Pooled analysis for continuous data",
      "topics": [
        "poolmodel_cont"
      ]
    },
    {
      "page": "powerprior_cont",
      "title": "Analysis for continuous data using the power prior approach",
      "topics": [
        "powerprior_cont"
      ]
    },
    {
      "page": "seasonal_trend",
      "title": "Generation of a seasonal trend",
      "topics": [
        "seasonal_trend"
      ]
    },
    {
      "page": "sepmodel_adj_bin",
      "title": "Separate analysis for binary data adjusted for periods",
      "topics": [
        "sepmodel_adj_bin"
      ]
    },
    {
      "page": "sepmodel_adj_cont",
      "title": "Separate analysis for continuous data adjusted for periods",
      "topics": [
        "sepmodel_adj_cont"
      ]
    },
    {
      "page": "sepmodel_bin",
      "title": "Separate analysis for binary data",
      "topics": [
        "sepmodel_bin"
      ]
    },
    {
      "page": "sepmodel_cont",
      "title": "Separate analysis for continuous data",
      "topics": [
        "sepmodel_cont"
      ]
    },
    {
      "page": "sim_study",
      "title": "Wrapper function performing simulation studies for a given set of scenarios (not parallelized)",
      "topics": [
        "sim_study"
      ]
    },
    {
      "page": "sim_study_par",
      "title": "Wrapper function performing simulation studies for a given set of scenarios (parallelized on replication level)",
      "topics": [
        "sim_study_par"
      ]
    },
    {
      "page": "splines_cal_cont",
      "title": "Spline regression analysis for continuous data with knots placed according to calendar time units",
      "topics": [
        "splines_cal_cont"
      ]
    },
    {
      "page": "splines_cont",
      "title": "Spline regression analysis for continuous data with knots placed according to periods",
      "topics": [
        "splines_cont"
      ]
    },
    {
      "page": "sw_trend",
      "title": "Generation of stepwise trend with equal jumps between periods",
      "topics": [
        "sw_trend"
      ]
    },
    {
      "page": "timemachine_bin",
      "title": "Time machine analysis for binary data",
      "topics": [
        "timemachine_bin"
      ]
    },
    {
      "page": "timemachine_cont",
      "title": "Time machine analysis for continuous data",
      "topics": [
        "timemachine_cont"
      ]
    }
  ],
  "_readme": "https://github.com/pavlakrotka/ncc/raw/HEAD/README.md",
  "_rundeps": [
    "abind",
    "assertthat",
    "backports",
    "bayesplot",
    "BayesPPD",
    "BH",
    "boot",
    "callr",
    "checkmate",
    "cli",
    "coda",
    "codetools",
    "cpp11",
    "desc",
    "digest",
    "distributional",
    "doFuture",
    "dplyr",
    "farver",
    "foreach",
    "Formula",
    "future",
    "future.apply",
    "generics",
    "geometry",
    "ggplot2",
    "ggridges",
    "globals",
    "glue",
    "gmp",
    "gridExtra",
    "gtable",
    "inline",
    "isoband",
    "iterators",
    "jsonlite",
    "labeling",
    "lattice",
    "lifecycle",
    "linprog",
    "listenv",
    "lme4",
    "lmerTest",
    "loo",
    "lpSolve",
    "magic",
    "magrittr",
    "MASS",
    "Matrix",
    "matrixStats",
    "mgcv",
    "minqa",
    "mvtnorm",
    "nlme",
    "nloptr",
    "numDeriv",
    "parallelly",
    "pbapply",
    "pillar",
    "pkgbuild",
    "pkgconfig",
    "plyr",
    "posterior",
    "processx",
    "proxy",
    "ps",
    "purrr",
    "QuickJSR",
    "R6",
    "RBesT",
    "rbibutils",
    "RColorBrewer",
    "Rcpp",
    "RcppArmadillo",
    "RcppEigen",
    "RcppNumerical",
    "RcppParallel",
    "RcppProgress",
    "Rdpack",
    "reformulas",
    "registry",
    "reshape2",
    "rjags",
    "rlang",
    "ROI",
    "rstan",
    "rstantools",
    "S7",
    "scales",
    "slam",
    "spaMM",
    "StanHeaders",
    "stringi",
    "stringr",
    "tensorA",
    "tibble",
    "tidyr",
    "tidyselect",
    "utf8",
    "vctrs",
    "viridisLite",
    "withr"
  ],
  "_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\nJAGS is Just Another Gibbs Sampler.  It is a program for analysis of\nBayesian hierarchical models using Markov Chain Monte Carlo (MCMC)\nsimulation not wholly unlike BUGS.\n\nJAGS was written with three aims in mind:\n* To have an engine for the BUGS language that runs on Unix\n* To be extensible, allowing users to write their own functions,\ndistributions and samplers.\n* To be a plaftorm for experimentation with ideas in Bayesian modelling\n\nThis package contains the 'jags' binary as well as the associated\nshared library modules loaded by the 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": "installation.Rmd",
      "filename": "installation.html",
      "title": "How to install the NCC package",
      "engine": "knitr::rmarkdown",
      "headings": [
        "1) Installing JAGS",
        "2) Installing the NCC package",
        "2a) from CRAN",
        "2b) from GitHub"
      ],
      "created": "2023-05-15 16:23:09",
      "modified": "2023-05-16 13:33:35",
      "commits": 2
    },
    {
      "source": "how_to_run_sim_study.Rmd",
      "filename": "how_to_run_sim_study.html",
      "title": "How to run a simulation study",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Preparing scenarios",
        "Running simulations",
        "Simulation results",
        "Type I error",
        "Bias",
        "MSE"
      ],
      "created": "2022-12-13 19:36:45",
      "modified": "2023-02-19 15:47:49",
      "commits": 4
    },
    {
      "source": "datasim_bin.Rmd",
      "filename": "datasim_bin.html",
      "title": "How to simulate binary data",
      "engine": "knitr::rmarkdown",
      "headings": [
        "datasim_bin()",
        "Assumptions",
        "Notation",
        "Usage",
        "Input",
        "Output",
        "Examples"
      ],
      "created": "2022-03-09 16:11:58",
      "modified": "2022-12-13 22:00:54",
      "commits": 11
    },
    {
      "source": "datasim_cont.Rmd",
      "filename": "datasim_cont.html",
      "title": "How to simulate continuous data",
      "engine": "knitr::rmarkdown",
      "headings": [
        "datasim_cont()",
        "Assumptions",
        "Notation",
        "Usage",
        "Input",
        "Output",
        "Examples"
      ],
      "created": "2022-03-07 09:51:21",
      "modified": "2022-12-13 22:00:54",
      "commits": 12
    },
    {
      "source": "ncc_intro.Rmd",
      "filename": "ncc_intro.html",
      "title": "NCC Introduction",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Non-concurrent controls in platform trials"
      ],
      "created": "2022-12-13 22:00:54",
      "modified": "2023-06-15 15:23:21",
      "commits": 4
    }
  ],
  "_score": 5.8750612633917,
  "_indexed": true,
  "_nocasepkg": "ncc",
  "_universes": [
    "pavlakrotka"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "1.0",
      "date": "2026-05-24T06:59:03.000Z",
      "distro": "noble",
      "commit": "f439de7b785d13669add0ba53666c96bd4d0b95f",
      "fileid": "5ffb983027c6c585af0ba31279edcf633321eb29b67bfdd498c1c838f0692f45",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/pavlakrotka/actions/runs/26354439911"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "1.0",
      "date": "2026-05-24T06:59:05.000Z",
      "distro": "noble",
      "commit": "f439de7b785d13669add0ba53666c96bd4d0b95f",
      "fileid": "56a44b24843d114448461449e7e02829034d076e1885facf9bc52a0153cfbf53",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/pavlakrotka/actions/runs/26354439911"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "1.0",
      "date": "2026-05-24T07:07:32.000Z",
      "commit": "f439de7b785d13669add0ba53666c96bd4d0b95f",
      "fileid": "383ce839a5d08c80e31408a169de2094f471ac91d4f56f78005ac347fca24729",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/pavlakrotka/actions/runs/26354439911"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "1.0",
      "date": "2026-05-24T07:07:51.000Z",
      "commit": "f439de7b785d13669add0ba53666c96bd4d0b95f",
      "fileid": "b33a2e7baa1f9994ff845e7d036a3d13cfb86626ba621d74fe139b1b6a87161f",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/pavlakrotka/actions/runs/26354439911"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "1.0",
      "date": "2026-05-24T06:58:56.000Z",
      "commit": "f439de7b785d13669add0ba53666c96bd4d0b95f",
      "fileid": "008d7129017313e73ca63f9435f9c0e5ae9043e375e5021b536c8b24aacb31fc",
      "status": "success",
      "buildurl": "https://github.com/r-universe/pavlakrotka/actions/runs/26354439911"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "1.0",
      "date": "2026-05-24T06:57:54.000Z",
      "commit": "f439de7b785d13669add0ba53666c96bd4d0b95f",
      "fileid": "8782c12d27ba15b2a05688c325447aff9a9006d53bbfb20eeb629f674c5504c0",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/pavlakrotka/actions/runs/26354439911"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "1.0",
      "date": "2026-05-24T06:58:02.000Z",
      "commit": "f439de7b785d13669add0ba53666c96bd4d0b95f",
      "fileid": "005455049d0d299e5480e0720f89eed7716b25a8ac418f6e63bd409685e525c6",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/pavlakrotka/actions/runs/26354439911"
    },
    {
      "r": "4.6.0",
      "os": "win",
      "version": "1.0",
      "date": "2026-05-24T06:58:09.000Z",
      "commit": "f439de7b785d13669add0ba53666c96bd4d0b95f",
      "fileid": "01f51e355b61d28c68893f0c01d84d3fb75db10b8b41a91865644c26b28fbcd9",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/pavlakrotka/actions/runs/26354439911"
    }
  ]
}