{
  "_id": "6a17edc5acfb0bcc41da4eee",
  "Package": "irrCAC",
  "Authors@R": "person(given = c(\"Kilem\", \"L.\"),\nfamily = \"Gwet\",\nrole = c(\"aut\", \"cre\"),\nemail = \"gwet@agreestat.com\")",
  "Version": "1.4",
  "Date": "2026-04-26",
  "Title": "Computing the Extent of Agreement among Raters with\nChance-Corrected Agreement Coefficient (CAC)",
  "Description": "Contains a series of R functions for calculating various\nchance-corrected agreement coefficients (CAC) among 2 or more\nraters. Among the CAC coefficients covered are Cohen's kappa,\nConger's kappa, Fleiss' kappa, Brennan-Prediger coefficient,\nGwet's AC1/AC2 coefficients, and Krippendorff's alpha. Multiple\nsets of weights are proposed for computing weighted analyses.\nAlso included in this package is Bangdiwala's B coefficient.",
  "Encoding": "UTF-8",
  "Language": "en-US",
  "LazyData": "true",
  "License": "GPL (>= 2)",
  "RoxygenNote": "7.3.3",
  "VignetteBuilder": "knitr",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-28 06:39:19 UTC",
    "User": "root"
  },
  "Author": "Kilem L. Gwet [aut, cre]",
  "Maintainer": "Kilem L. Gwet <gwet@agreestat.com>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-04-27 09:33:47 UTC",
  "RemoteUrl": "https://github.com/cran/irrCAC",
  "RemoteRef": "HEAD",
  "RemoteSha": "720ab226e407e238bf85f86e9458b93e7793e8a3",
  "MD5sum": "5067b23c9e7a3234e1a5e9ca8a72334d",
  "_user": "cran",
  "_type": "src",
  "_file": "irrCAC_1.4.tar.gz",
  "_fileid": "667733f97c23084841d440d8bfbccf6087e289459b6ebac9a328efe26ea2b485",
  "_filesize": 756543,
  "_sha256": "667733f97c23084841d440d8bfbccf6087e289459b6ebac9a328efe26ea2b485",
  "_created": "2026-05-28T06:39:19.000Z",
  "_published": "2026-05-28T07:24:53.911Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 78237455382,
      "time": 132,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7259331246"
    },
    {
      "job": 78237455393,
      "time": 2691,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7260004445"
    },
    {
      "job": 78237027646,
      "time": 211,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7259298041"
    },
    {
      "job": 78237455387,
      "time": 105,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7259324611"
    }
  ],
  "_buildurl": "https://github.com/r-universe/cran/actions/runs/26558927816",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cran/irrCAC",
  "_commit": {
    "id": "720ab226e407e238bf85f86e9458b93e7793e8a3",
    "author": "Kilem L. Gwet <gwet@agreestat.com>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 1.4\n",
    "time": 1777282427
  },
  "_maintainer": {
    "name": "Kilem L. Gwet",
    "email": "gwet@agreestat.com"
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.5.0",
      "role": "Depends"
    },
    {
      "package": "dplyr",
      "role": "Imports"
    },
    {
      "package": "magrittr",
      "role": "Imports"
    },
    {
      "package": "tidyr",
      "role": "Imports"
    },
    {
      "package": "stringr",
      "role": "Imports"
    },
    {
      "package": "tibble",
      "role": "Imports"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "spelling",
      "role": "Suggests"
    }
  ],
  "_owner": "cran",
  "_selfowned": false,
  "_usedby": 2,
  "_updates": [
    {
      "week": "2026-18",
      "n": 1
    }
  ],
  "_tags": [
    {
      "name": "1.4",
      "date": "2026-04-27"
    }
  ],
  "_stars": 0,
  "_userbio": {
    "uuid": 6899542,
    "type": "organization",
    "name": "cran",
    "description": "Unofficial read-only mirror of all CRAN R packages"
  },
  "_downloads": {
    "count": 1352,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/irrCAC"
  },
  "_mentions": 4,
  "_searchresults": 108,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/irrCAC.html",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_realowner": "cran",
  "_cranurl": false,
  "_releases": [
    {
      "version": "1.0",
      "date": "2019-09-23"
    },
    {
      "version": "1.4",
      "date": "2026-04-27"
    }
  ],
  "_exports": [
    "altman.bf",
    "bangdiwala.table",
    "bangdiwala2RR.fn",
    "bipolar.weights",
    "bp.coeff.dist",
    "bp.coeff.raw",
    "bp2.table",
    "circular.weights",
    "conger.kappa.raw",
    "fleiss.bf",
    "fleiss.kappa.dist",
    "fleiss.kappa.raw",
    "freq.supp.fn",
    "gwet.ac1.dist",
    "gwet.ac1.raw",
    "gwet.ac1.table",
    "identity.weights",
    "kappa2.table",
    "krippen.alpha.dist",
    "krippen.alpha.raw",
    "krippen2.table",
    "landis.koch.bf",
    "linear.weights",
    "long2wide.fn",
    "ordinal.weights",
    "pa.coeff.dist",
    "pa.coeff.raw",
    "pa2.table",
    "quadratic.weights",
    "radical.weights",
    "ratio.weights",
    "scott2.table"
  ],
  "_datasets": [
    {
      "name": "agree.cac3rd",
      "title": "Dataset showing the distribution of 6 raters by psychiatric condition",
      "object": "agreeCAC3rd",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Gender",
        "Depression",
        "Pers.Disorder",
        "Schizophrenia",
        "Neurosis",
        "Other"
      ],
      "rows": 15,
      "table": true,
      "tojson": true
    },
    {
      "name": "agree.contingency",
      "title": "Dataset representing a 10x10 contingency table",
      "object": "agreeContingency",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Categories",
        "C1",
        "C2",
        "C3",
        "C4",
        "C5",
        "C6",
        "C7",
        "C8",
        "C9",
        "C10"
      ],
      "rows": 10,
      "table": true,
      "tojson": true
    },
    {
      "name": "agreeCAC",
      "title": "Ratings of 15 subjects from 4 raters",
      "object": "agreeCAC",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Group",
        "RaterA",
        "RaterB",
        "RaterC",
        "RaterD"
      ],
      "rows": 15,
      "table": true,
      "tojson": true
    },
    {
      "name": "altman",
      "title": "Dataset describing the Altman's Benchmarking Scale",
      "object": "altman",
      "class": [
        "data.frame"
      ],
      "fields": [
        "lb.AL",
        "ub.AL",
        "interp.AL"
      ],
      "rows": 5,
      "table": true,
      "tojson": true
    },
    {
      "name": "cac.ben.gerry",
      "title": "Ratings of 12 units from 2 raters named Ben and Gerry",
      "object": "cac.ben.gerry",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Group",
        "Units",
        "Ben",
        "Gerry"
      ],
      "rows": 12,
      "table": true,
      "tojson": true
    },
    {
      "name": "cac.dist.g1g2",
      "title": "Distribution of 4 raters by subject and by category, for 14 Subjects that belong to 2 groups \"G1\" and \"G2\"",
      "object": "cac.dist.g1g2",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Group",
        "Units",
        "a",
        "b",
        "c",
        "d",
        "e"
      ],
      "rows": 14,
      "table": true,
      "tojson": true
    },
    {
      "name": "cac.dist4cat",
      "title": "Distribution of 4 raters by Category and Subject - Subjects allocated in 2 groups A and B.",
      "object": "cac.dist4cat",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Group",
        "a",
        "b",
        "c"
      ],
      "rows": 15,
      "table": true,
      "tojson": true
    },
    {
      "name": "cac.raw.g1g2",
      "title": "Dataset of raw ratings from 4 Raters on 14 Subjects that belong to 2 groups named \"G1\" and \"G2\"",
      "object": "cac.raw.g1g2",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Group",
        "Units",
        "Rater1",
        "Rater2",
        "Rater3",
        "Rater4"
      ],
      "rows": 14,
      "table": true,
      "tojson": true
    },
    {
      "name": "cac.raw.gender",
      "title": "Rating Data from 4 Raters and 15 human Subjects, 9 of whom are female and 6 males.",
      "object": "cac.raw.gender",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Group",
        "RaterA",
        "RaterB",
        "RaterC",
        "RaterD"
      ],
      "rows": 15,
      "table": true,
      "tojson": true
    },
    {
      "name": "cac.raw2raters",
      "title": "Dataset of raw ratings by 2 raters and 12 subjects.",
      "object": "cac.raw2raters",
      "class": [
        "data.frame"
      ],
      "fields": [
        "rater1",
        "rater2"
      ],
      "rows": 12,
      "table": true,
      "tojson": true
    },
    {
      "name": "cac.raw4raters",
      "title": "Rating Data from 4 Raters and 12 Subjects.",
      "object": "cac.raw4raters",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Rater1",
        "Rater2",
        "Rater3",
        "Rater4"
      ],
      "rows": 12,
      "table": true,
      "tojson": true
    },
    {
      "name": "cac.raw5obser",
      "title": "Scores assigned by 5 observers to 20 experimental units.",
      "object": "cac.raw5obser",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Observer1",
        "Observer2",
        "Observer3",
        "Observer4",
        "Observer5"
      ],
      "rows": 15,
      "table": true,
      "tojson": true
    },
    {
      "name": "cont3x3abstractors",
      "title": "Distribution of 100 pregnant women by pregnancy type and by abstractor.",
      "object": "cont3x3abstractors",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Ectopic",
        "AIU",
        "NIU"
      ],
      "rows": 3,
      "table": true,
      "tojson": true
    },
    {
      "name": "cont4x4diagnosis",
      "title": "Distribution of 223 Psychiatric Patients by Type of of Psychiatric Disorder and Diagnosis Method.",
      "object": "cont4x4diagnosis",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Schizophrenia",
        "Bipolar.Disorder",
        "Depression",
        "Other"
      ],
      "rows": 4,
      "table": true,
      "tojson": true
    },
    {
      "name": "distrib.6raters",
      "title": "Distribution of 6 psychiatrists by Subject/patient and diagnosis Category.",
      "object": "distrib.6raters",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Depression",
        "Personality.Disorder",
        "Schizophrenia",
        "Neurosis",
        "Other"
      ],
      "rows": 15,
      "table": true,
      "tojson": true
    },
    {
      "name": "fleiss",
      "title": "Dataset describing Fleiss' Benchmarking Scale",
      "object": "fleiss",
      "class": [
        "data.frame"
      ],
      "fields": [
        "lb.FL",
        "ub.FL",
        "interp.FL"
      ],
      "rows": 3,
      "table": true,
      "tojson": true
    },
    {
      "name": "freqs.data",
      "title": "Distribution of 10 subjects by rater (Ben and Gerry) and by category.",
      "object": "freqs.data",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Ben",
        "Gerry",
        "n"
      ],
      "rows": 7,
      "table": true,
      "tojson": true
    },
    {
      "name": "landis.koch",
      "title": "Dataset describing the Landis & Koch Benchmarking Scale",
      "object": "landis.koch",
      "class": [
        "data.frame"
      ],
      "fields": [
        "lb.LK",
        "ub.LK",
        "interp.LK"
      ],
      "rows": 6,
      "table": true,
      "tojson": true
    },
    {
      "name": "x.dist10x5",
      "title": "Dataset of categorical ratings assigned to 10 subjects and presented in the form of a distribution of 4 raters by subject and category",
      "object": "x.dist10x5",
      "class": [
        "data.frame"
      ],
      "fields": [
        "subject",
        "q1",
        "q2",
        "q3",
        "q4",
        "q5"
      ],
      "rows": 10,
      "table": true,
      "tojson": true
    },
    {
      "name": "x.dist6x5psy",
      "title": "Dataset showing how 6 psychiatrists classified 15 patients by their mental health condition.",
      "object": "x.dist6x5psy",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Subject",
        "Depression",
        "Personality.Disorder",
        "Schizophrenia",
        "Neurosis",
        "Other"
      ],
      "rows": 15,
      "table": true,
      "tojson": true
    },
    {
      "name": "x.raw10x4",
      "title": "Raw categorical ratings assigned to 10 subjects by 4 raters",
      "object": "x.raw10x4",
      "class": [
        "data.frame"
      ],
      "fields": [
        "subject",
        "rater1",
        "rater2",
        "rater3",
        "rater4"
      ],
      "rows": 10,
      "table": true,
      "tojson": true
    },
    {
      "name": "x.raw12x4",
      "title": "This dataset contains raw categorical ratings that 4 raters assigned to 12 subjects.",
      "object": "x.raw12x4",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Units",
        "Rater1",
        "Rater2",
        "Rater3",
        "Rater4"
      ],
      "rows": 12,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "agree.cac3rd",
      "title": "Dataset showing the distribution of 6 raters by psychiatric condition",
      "topics": [
        "agree.cac3rd"
      ]
    },
    {
      "page": "agree.contingency",
      "title": "Dataset representing a 10x10 contingency table",
      "topics": [
        "agree.contingency"
      ]
    },
    {
      "page": "agreeCAC",
      "title": "Ratings of 15 subjects from 4 raters",
      "topics": [
        "agreeCAC"
      ]
    },
    {
      "page": "altman",
      "title": "Dataset describing the Altman's Benchmarking Scale",
      "topics": [
        "altman"
      ]
    },
    {
      "page": "altman.bf",
      "title": "Computing Altman's Benchmark Scale Membership Probabilities",
      "topics": [
        "altman.bf"
      ]
    },
    {
      "page": "bangdiwala.table",
      "title": "Bangdiwala B coefficient for 2 raters",
      "topics": [
        "bangdiwala.table"
      ]
    },
    {
      "page": "bangdiwala2RR.fn",
      "title": "Bangdiwala B coefficient for 2 raters when input dataset is made up of 2 columns of raw data.",
      "topics": [
        "bangdiwala2RR.fn"
      ]
    },
    {
      "page": "bipolar.weights",
      "title": "Function for computing the Bipolar Weights",
      "topics": [
        "bipolar.weights"
      ]
    },
    {
      "page": "bp.coeff.dist",
      "title": "Brennan-Prediger's agreement coefficient among multiple raters (2, 3, +) when the input dataset is the distribution of raters by subject and category.",
      "topics": [
        "bp.coeff.dist"
      ]
    },
    {
      "page": "bp.coeff.raw",
      "title": "Brennan & Prediger's (BP) agreement coefficient for an arbitrary number of raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.",
      "topics": [
        "bp.coeff.raw"
      ]
    },
    {
      "page": "bp2.table",
      "title": "Brenann-Prediger coefficient for 2 raters",
      "topics": [
        "bp2.table"
      ]
    },
    {
      "page": "cac.ben.gerry",
      "title": "Ratings of 12 units from 2 raters named Ben and Gerry",
      "topics": [
        "cac.ben.gerry"
      ]
    },
    {
      "page": "cac.dist.g1g2",
      "title": "Distribution of 4 raters by subject and by category, for 14 Subjects that belong to 2 groups \"G1\" and \"G2\"",
      "topics": [
        "cac.dist.g1g2"
      ]
    },
    {
      "page": "cac.dist4cat",
      "title": "Distribution of 4 raters by Category and Subject - Subjects allocated in 2 groups A and B.",
      "topics": [
        "cac.dist4cat"
      ]
    },
    {
      "page": "cac.raw.g1g2",
      "title": "Dataset of raw ratings from 4 Raters on 14 Subjects that belong to 2 groups named \"G1\" and \"G2\"",
      "topics": [
        "cac.raw.g1g2"
      ]
    },
    {
      "page": "cac.raw.gender",
      "title": "Rating Data from 4 Raters and 15 human Subjects, 9 of whom are female and 6 males.",
      "topics": [
        "cac.raw.gender"
      ]
    },
    {
      "page": "cac.raw2raters",
      "title": "Dataset of raw ratings by 2 raters and 12 subjects.",
      "topics": [
        "cac.raw2raters"
      ]
    },
    {
      "page": "cac.raw4raters",
      "title": "Rating Data from 4 Raters and 12 Subjects.",
      "topics": [
        "cac.raw4raters"
      ]
    },
    {
      "page": "cac.raw5obser",
      "title": "Scores assigned by 5 observers to 20 experimental units.",
      "topics": [
        "cac.raw5obser"
      ]
    },
    {
      "page": "circular.weights",
      "title": "Function for computing the Circular Weights",
      "topics": [
        "circular.weights"
      ]
    },
    {
      "page": "conger.kappa.raw",
      "title": "Conger's generalized kappa coefficient for an arbitrary number of raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.",
      "topics": [
        "conger.kappa.raw"
      ]
    },
    {
      "page": "cont3x3abstractors",
      "title": "Distribution of 100 pregnant women by pregnancy type and by abstractor.",
      "topics": [
        "cont3x3abstractors"
      ]
    },
    {
      "page": "cont4x4diagnosis",
      "title": "Distribution of 223 Psychiatric Patients by Type of of Psychiatric Disorder and Diagnosis Method.",
      "topics": [
        "cont4x4diagnosis"
      ]
    },
    {
      "page": "distrib.6raters",
      "title": "Distribution of 6 psychiatrists by Subject/patient and diagnosis Category.",
      "topics": [
        "distrib.6raters"
      ]
    },
    {
      "page": "fleiss",
      "title": "Dataset describing Fleiss' Benchmarking Scale",
      "topics": [
        "fleiss"
      ]
    },
    {
      "page": "fleiss.bf",
      "title": "Computing Fleiss Benchmark Scale Membership Probabilities",
      "topics": [
        "fleiss.bf"
      ]
    },
    {
      "page": "fleiss.kappa.dist",
      "title": "Fleiss' agreement coefficient among multiple raters (2, 3, +) when the input dataset is the distribution of raters by subject and category.",
      "topics": [
        "fleiss.kappa.dist"
      ]
    },
    {
      "page": "fleiss.kappa.raw",
      "title": "Fleiss' generalized kappa among multiple raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.",
      "topics": [
        "fleiss.kappa.raw"
      ]
    },
    {
      "page": "freq.supp.fn",
      "title": "freq.supp.fn: This function reads a 3-variable input data file containing unique pairs of categories along with their frequency of occurrences, and outputs a similar file where all possible pairs of categories are represented, some with a frequency of occurrence of 0.",
      "topics": [
        "freq.supp.fn"
      ]
    },
    {
      "page": "freqs.data",
      "title": "Distribution of 10 subjects by rater (Ben and Gerry) and by category.",
      "topics": [
        "freqs.data"
      ]
    },
    {
      "page": "gwet.ac1.dist",
      "title": "Gwet's AC1/AC2 agreement coefficient among multiple raters (2, 3, +) when the input dataset is the distribution of raters by subject and category.",
      "topics": [
        "gwet.ac1.dist"
      ]
    },
    {
      "page": "gwet.ac1.raw",
      "title": "Gwet's AC1/AC2 agreement coefficient among multiple raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.",
      "topics": [
        "gwet.ac1.raw"
      ]
    },
    {
      "page": "gwet.ac1.table",
      "title": "Gwet's AC1/AC2 coefficient for 2 raters",
      "topics": [
        "gwet.ac1.table"
      ]
    },
    {
      "page": "identity.weights",
      "title": "Function for computing the Identity Weights",
      "topics": [
        "identity.weights"
      ]
    },
    {
      "page": "kappa2.table",
      "title": "Kappa coefficient for 2 raters",
      "topics": [
        "kappa2.table"
      ]
    },
    {
      "page": "krippen.alpha.dist",
      "title": "Krippendorff's agreement coefficient among multiple raters (2, 3, +) when the input dataset is the distribution of raters by subject and category.",
      "topics": [
        "krippen.alpha.dist"
      ]
    },
    {
      "page": "krippen.alpha.raw",
      "title": "Krippendorff's alpha coefficient for an arbitrary number of raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.",
      "topics": [
        "krippen.alpha.raw"
      ]
    },
    {
      "page": "krippen2.table",
      "title": "Krippendorff's Alpha coefficient for 2 raters",
      "topics": [
        "krippen2.table"
      ]
    },
    {
      "page": "landis.koch",
      "title": "Dataset describing the Landis & Koch Benchmarking Scale",
      "topics": [
        "landis.koch"
      ]
    },
    {
      "page": "landis.koch.bf",
      "title": "Computing Landis-Koch Benchmark Scale Membership Probabilities",
      "topics": [
        "landis.koch.bf"
      ]
    },
    {
      "page": "linear.weights",
      "title": "Function for computing the Linear Weights",
      "topics": [
        "linear.weights"
      ]
    },
    {
      "page": "long2wide.fn",
      "title": "long2wide.fn: This function transforms a 3-column dataset of frequencies to a square matrix or a contingency table. This function uses the freq.supp.fn() function.",
      "topics": [
        "long2wide.fn"
      ]
    },
    {
      "page": "ordinal.weights",
      "title": "Function for computing the Ordinal Weights",
      "topics": [
        "ordinal.weights"
      ]
    },
    {
      "page": "pa.coeff.dist",
      "title": "Percent agreement coefficient among multiple raters (2, 3, +) when the input dataset is the distribution of raters by subject and category.",
      "topics": [
        "pa.coeff.dist"
      ]
    },
    {
      "page": "pa.coeff.raw",
      "title": "Percent agreement among multiple raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.",
      "topics": [
        "pa.coeff.raw"
      ]
    },
    {
      "page": "pa2.table",
      "title": "Percent Agreement coefficient for 2 raters",
      "topics": [
        "pa2.table"
      ]
    },
    {
      "page": "quadratic.weights",
      "title": "Function for computing the Quadratic Weights",
      "topics": [
        "quadratic.weights"
      ]
    },
    {
      "page": "radical.weights",
      "title": "Function for computing the Radical Weights",
      "topics": [
        "radical.weights"
      ]
    },
    {
      "page": "ratio.weights",
      "title": "Function for computing the Ratio Weights",
      "topics": [
        "ratio.weights"
      ]
    },
    {
      "page": "scott2.table",
      "title": "Scott's coefficient for 2 raters",
      "topics": [
        "scott2.table"
      ]
    },
    {
      "page": "trim",
      "title": "An r function for trimming leading and trealing blanks",
      "topics": [
        "trim"
      ]
    },
    {
      "page": "x.dist10x5",
      "title": "Dataset of categorical ratings assigned to 10 subjects and presented in the form of a distribution of 4 raters by subject and category",
      "topics": [
        "x.dist10x5"
      ]
    },
    {
      "page": "x.dist6x5psy",
      "title": "Dataset showing how 6 psychiatrists classified 15 patients by their mental health condition.",
      "topics": [
        "x.dist6x5psy"
      ]
    },
    {
      "page": "x.raw10x4",
      "title": "Raw categorical ratings assigned to 10 subjects by 4 raters",
      "topics": [
        "x.raw10x4"
      ]
    },
    {
      "page": "x.raw12x4",
      "title": "This dataset contains raw categorical ratings that 4 raters assigned to 12 subjects.",
      "topics": [
        "x.raw12x4"
      ]
    }
  ],
  "_readme": "https://github.com/cran/irrCAC/raw/HEAD/README.md",
  "_rundeps": [
    "cli",
    "cpp11",
    "dplyr",
    "generics",
    "glue",
    "lifecycle",
    "magrittr",
    "pillar",
    "pkgconfig",
    "purrr",
    "R6",
    "rlang",
    "stringi",
    "stringr",
    "tibble",
    "tidyr",
    "tidyselect",
    "utf8",
    "vctrs",
    "withr"
  ],
  "_vignettes": [
    {
      "source": "benchmarking.Rmd",
      "filename": "benchmarking.html",
      "title": "irrCAC-benchmarking",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Abstract",
        "",
        "Interpreting the magnitude of agreement coeeficients",
        "References:"
      ],
      "created": "2019-09-23 14:10:02",
      "modified": "2026-04-27 09:33:47",
      "commits": 2
    },
    {
      "source": "overview.Rmd",
      "filename": "overview.html",
      "title": "Calculating Chance-corrected Agreement Coefficients (CAC)",
      "author": "Kilem L. Gwet, Ph.D.",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Abstract",
        "Computing Agreement Coefficients",
        "Computing agreement Coefficients from Contingency tables",
        "Computing agreement coefficients from the distribution of raters by subject & category",
        "Computing agreement coefficients from raw ratings",
        "References:"
      ],
      "created": "2019-09-23 14:10:02",
      "modified": "2026-04-27 09:33:47",
      "commits": 2
    },
    {
      "source": "weighting.Rmd",
      "filename": "weighting.html",
      "title": "Weighted Chance-corrected Agreement Coefficients",
      "author": "Kilem L. Gwet, Ph.D.",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Abstract",
        "",
        "The different weights",
        "Weighted Agreement Coefficients",
        "Weighting ratings from a contingency table",
        "Weighting for a dataset of raw ratings",
        "Weighting when input data is the distribution of raters by subject and rating",
        "References:"
      ],
      "created": "2019-09-23 14:10:02",
      "modified": "2026-04-27 09:33:47",
      "commits": 2
    }
  ],
  "_score": 5.720702947859854,
  "_indexed": true,
  "_nocasepkg": "irrcac",
  "_universes": [
    "cran"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "1.4",
      "date": "2026-05-28T06:41:25.000Z",
      "distro": "noble",
      "commit": "720ab226e407e238bf85f86e9458b93e7793e8a3",
      "fileid": "8151da129503ae40f4f5af11b442f70af5cdcf73c8df4f761007c3822aac9b00",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/26558927816"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "1.4",
      "date": "2026-05-28T07:24:06.000Z",
      "distro": "noble",
      "commit": "720ab226e407e238bf85f86e9458b93e7793e8a3",
      "fileid": "ed67b236b7565d6cea4050c7564a597dd3c6f2265da434b2496004fc7073b774",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/26558927816"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "1.4",
      "date": "2026-05-28T06:41:26.000Z",
      "commit": "720ab226e407e238bf85f86e9458b93e7793e8a3",
      "fileid": "8182a49f3ec48a4e83a68d57ee3743e4057f0e89805e8c5b717a8d64758f59c1",
      "status": "success",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/26558927816"
    }
  ]
}