{
  "_id": "6a1efd69b401979e73419b6b",
  "Package": "subscore",
  "Title": "Computing Subscores in Classical Test Theory and Item Response\nTheory",
  "Version": "3.3",
  "Authors@R": "c(person(\"Shenghai\", \"Dai\", role = c(\"aut\", \"cre\"), \nemail = \"s.dai@wsu.edu\"),\nperson(\"Xiaolin\", \"Wang\", role = \"aut\"),\nperson(\"Dubravka\", \"Svetina\", role = \"aut\"))",
  "Author": "Shenghai Dai [aut, cre], Xiaolin Wang [aut], Dubravka Svetina\n[aut]",
  "Maintainer": "Shenghai Dai <s.dai@wsu.edu>",
  "Description": "Functions for computing test subscores using different\nmethods in both classical test theory (CTT) and item response\ntheory (IRT). This package enables three types of subscoring\nmethods within the framework of CTT and IRT, including (1)\nWainer's augmentation method (Wainer et. al., 2001)\n<doi:10.4324/9781410604729>, (2) Haberman's subscoring methods\n(Haberman, 2008) <doi:10.3102/1076998607302636>, and (3) Yen's\nobjective performance index (OPI; Yen, 1987)\n<https://www.ets.org/research/policy_research_reports/publications/paper/1987/hrap>.\nIt also includes functions to compute Proportional Reduction of\nMean Squared Errors (PRMSEs) in Haberman's methods which are\nused to examine whether test subscores are of added value. In\naddition, the package includes a function to assess the local\nindependence assumption of IRT with Yen's Q3 statistic (Yen,\n1984 <doi:10.1177/014662168400800201>; Yen, 1993\n<doi:10.1111/j.1745-3984.1993.tb00423.x>).",
  "NeedsCompilation": "no",
  "LazyData": "true",
  "Encoding": "UTF-8",
  "License": "GPL (>= 2)",
  "RoxygenNote": "7.2.0",
  "Packaged": {
    "Date": "2026-05-18 09:55:21 UTC",
    "User": "root"
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  "Repository": "https://daiscode.r-universe.dev",
  "Date/Publication": "2022-05-24 10:00:07 UTC",
  "RemoteUrl": "https://github.com/cran/subscore",
  "RemoteRef": "HEAD",
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  "_user": "daiscode",
  "_type": "src",
  "_file": "subscore_3.3.tar.gz",
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  "_created": "2026-05-18T09:55:21.000Z",
  "_published": "2026-06-02T15:57:29.728Z",
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  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cran/subscore",
  "_commit": {
    "id": "e84c61801a0c7d54910aebc866d510b9d911b374",
    "author": "Shenghai Dai <s.dai@wsu.edu>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 3.3\n",
    "time": 1653386407
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  "_maintainer": {
    "name": "Shenghai Dai",
    "email": "s.dai@wsu.edu",
    "login": "daiscode",
    "linkedin": "in/shenghaidai",
    "description": "",
    "uuid": 65202496
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  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.4.0",
      "role": "Depends"
    },
    {
      "package": "CTT",
      "role": "Depends"
    },
    {
      "package": "stats",
      "role": "Depends"
    },
    {
      "package": "irtoys",
      "role": "Depends"
    },
    {
      "package": "sirt",
      "role": "Depends"
    },
    {
      "package": "ltm",
      "role": "Depends"
    },
    {
      "package": "cocor",
      "role": "Imports"
    },
    {
      "package": "boot",
      "role": "Imports"
    }
  ],
  "_owner": "cran",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_stars": 1,
  "_contributors": [
    {
      "user": "daiscode",
      "count": 3,
      "uuid": 65202496
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  ],
  "_userbio": {
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    "type": "user",
    "name": "Dai"
  },
  "_downloads": {
    "count": 383,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/subscore"
  },
  "_mentions": 1,
  "_searchresults": 12,
  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/subscore.html",
    "manual.pdf"
  ],
  "_realowner": "daiscode",
  "_cranurl": false,
  "_releases": [
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      "version": "1.1",
      "date": "2015-08-19"
    },
    {
      "version": "1.2",
      "date": "2015-11-21"
    },
    {
      "version": "1.3",
      "date": "2016-08-17"
    },
    {
      "version": "2.0",
      "date": "2016-12-02"
    },
    {
      "version": "3.0",
      "date": "2019-03-04"
    },
    {
      "version": "3.1",
      "date": "2019-04-13"
    },
    {
      "version": "3.3",
      "date": "2022-05-24"
    }
  ],
  "_exports": [
    "CTTsub",
    "data.prep",
    "subscore.corr",
    "subscore.s",
    "subscore.sx",
    "subscore.Wainer",
    "subscore.x",
    "Yen.OPI",
    "Yen.Q3"
  ],
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    {
      "name": "scored.data",
      "title": "Sample scored data",
      "object": "scored.data",
      "class": [
        "data.frame"
      ],
      "fields": [
        "V1",
        "V2",
        "V3",
        "V4",
        "V5",
        "V6",
        "V7",
        "V8",
        "V9",
        "V10",
        "V11",
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        "V15",
        "V16",
        "V17",
        "V18",
        "V19",
        "V20",
        "V21",
        "V22",
        "V23",
        "V24",
        "V25",
        "V26",
        "V27",
        "V28",
        "V29",
        "V30",
        "V31",
        "V32",
        "V33",
        "V34",
        "V35",
        "V36",
        "V37",
        "V38",
        "V39",
        "V40",
        "V41",
        "V42",
        "V43",
        "V44",
        "V45",
        "V46",
        "V47",
        "V48",
        "V49",
        "V50"
      ],
      "rows": 150,
      "table": true,
      "tojson": true
    },
    {
      "name": "test.data",
      "title": "A list of objects that include both test information and subscores.",
      "object": "test.data",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "TIMSS11G8M.data",
      "title": "The 2011 TIMSS Grade 8 Mathematics Assessment Dataset",
      "object": "TIMSS11G8M.data",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Q1",
        "Q2",
        "Q3",
        "Q4",
        "Q5",
        "Q6",
        "Q7",
        "Q8",
        "Q9",
        "Q10",
        "Q11",
        "Q12",
        "Q13",
        "Q14",
        "Q15",
        "Q16",
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        "Q19",
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        "Q21",
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        "Q29",
        "Q30",
        "Q31",
        "Q32"
      ],
      "rows": 765,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "CTTsub",
      "title": "This main function estimates true subscores using different methods based on original CTT scores.",
      "topics": [
        "CTTsub"
      ]
    },
    {
      "page": "data.prep",
      "title": "This function prepares data into a required list format",
      "topics": [
        "data.prep"
      ]
    },
    {
      "page": "scored.data",
      "title": "Sample scored data",
      "topics": [
        "scored.data"
      ]
    },
    {
      "page": "subscore.corr",
      "title": "Computing correlation indices for subscores and the total score.",
      "topics": [
        "subscore.corr"
      ]
    },
    {
      "page": "subscore.s",
      "title": "Computing subscores using Haberman's method based on observed subscores.",
      "topics": [
        "subscore.s"
      ]
    },
    {
      "page": "subscore.sx",
      "title": "Computing subscores using Haberman's method based on both observed total scores and observed subscores.",
      "topics": [
        "subscore.sx"
      ]
    },
    {
      "page": "subscore.Wainer",
      "title": "Estimating true subscores using Wainer's augmentation method",
      "topics": [
        "subscore.Wainer"
      ]
    },
    {
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      "title": "Computing subscores using Haberman's method based on observed total scores.",
      "topics": [
        "subscore.x"
      ]
    },
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      "topics": [
        "test.data"
      ]
    },
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    },
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      "title": "Estimating true subscores using Yen's OPI",
      "topics": [
        "Yen.OPI"
      ]
    },
    {
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      "title": "Computing Yen's Q3 statistic for unidimensional Rasch, 1-, 2-, and 3-PL logistic IRT models",
      "topics": [
        "Yen.Q3"
      ]
    }
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  "_nocasepkg": "subscore",
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