{
  "_id": "6a1f1909b401979e7341ee6c",
  "Package": "betaMC",
  "Title": "Monte Carlo for Regression Effect Sizes",
  "Version": "1.3.3",
  "Authors@R": "person(given = \"Ivan Jacob Agaloos\",\nfamily = \"Pesigan\",\nrole = c(\"aut\", \"cre\", \"cph\"),\nemail = \"r.jeksterslab@gmail.com\",\ncomment = c(ORCID = \"0000-0003-4818-8420\"))",
  "Description": "Generates Monte Carlo confidence intervals for\nstandardized regression coefficients (beta) and other effect\nsizes, including multiple correlation, semipartial\ncorrelations, improvement in R-squared, squared partial\ncorrelations, and differences in standardized regression\ncoefficients, for models fitted by lm(). 'betaMC' combines\nideas from Monte Carlo confidence intervals for the indirect\neffect (Pesigan and Cheung, 2024\n<doi:10.3758/s13428-023-02114-4>) and the sampling covariance\nmatrix of regression coefficients (Dudgeon, 2017\n<doi:10.1007/s11336-017-9563-z>) to generate confidence\nintervals effect sizes in regression.",
  "URL": "https://github.com/jeksterslab/betaMC,\nhttps://jeksterslab.github.io/betaMC/",
  "BugReports": "https://github.com/jeksterslab/betaMC/issues",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.3.3.9000",
  "Repository": "https://jeksterslab.r-universe.dev",
  "Date/Publication": "2025-10-19 02:45:20 UTC",
  "RemoteUrl": "https://github.com/jeksterslab/betaMC",
  "RemoteRef": "HEAD",
  "RemoteSha": "33f5368b43d0a0235b28385fad516fd1d5a69637",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-17 05:30:28 UTC",
    "User": "root"
  },
  "Author": "Ivan Jacob Agaloos Pesigan [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0003-4818-8420>)",
  "Maintainer": "Ivan Jacob Agaloos Pesigan <r.jeksterslab@gmail.com>",
  "MD5sum": "15e003bebff67617bd40d1b7ed607a17",
  "_user": "jeksterslab",
  "_type": "src",
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  "_created": "2026-05-17T05:30:28.000Z",
  "_published": "2026-06-02T17:55:21.923Z",
  "_distro": "noble",
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  "_updates": [
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      "n": 4
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      "name": "v1.3.3",
      "date": "2025-10-19"
    }
  ],
  "_topics": [
    "confidence-intervals",
    "monte-carlo",
    "regression-effect-sizes",
    "standardized-regression-coefficients"
  ],
  "_stars": 1,
  "_contributors": [
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    "extra/citation.cff",
    "extra/citation.html",
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    "extra/contents.json",
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  "_realowner": "jeksterslab",
  "_cranurl": true,
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      "date": "2023-01-09"
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      "date": "2023-04-13"
    },
    {
      "version": "1.3.0",
      "date": "2023-08-24"
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      "date": "2023-10-15"
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      "date": "2024-04-14"
    },
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    "DeltaRSqMC",
    "DiffBetaMC",
    "MC",
    "MCMI",
    "PCorMC",
    "RSqMC",
    "SCorMC"
  ],
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      "name": "nas1982",
      "title": "1982 National Academy of Sciences Doctoral Programs Data",
      "object": "nas1982",
      "class": [
        "data.frame"
      ],
      "fields": [
        "QUALITY",
        "NFACUL",
        "NGRADS",
        "PCTSUPP",
        "PCTGRT",
        "NARTIC",
        "PCTPUB"
      ],
      "rows": 46,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "BetaMC",
      "title": "Estimate Standardized Regression Coefficients and Generate the Corresponding Sampling Distribution Using the Monte Carlo Method",
      "concept": [
        "Beta Monte Carlo Functions"
      ],
      "topics": [
        "BetaMC"
      ]
    },
    {
      "page": "coef.betamc",
      "title": "Estimated Parameter Method for an Object of Class 'betamc'",
      "topics": [
        "coef.betamc"
      ]
    },
    {
      "page": "confint.betamc",
      "title": "Confidence Intervals Method for an Object of Class 'betamc'",
      "topics": [
        "confint.betamc"
      ]
    },
    {
      "page": "DeltaRSqMC",
      "title": "Estimate Improvement in R-Squared and Generate the Corresponding Sampling Distribution Using the Monte Carlo Method",
      "concept": [
        "Beta Monte Carlo Functions"
      ],
      "topics": [
        "DeltaRSqMC"
      ]
    },
    {
      "page": "DiffBetaMC",
      "title": "Estimate Differences of Standardized Slopes and Generate the Corresponding Sampling Distribution Using the Monte Carlo Method",
      "concept": [
        "Beta Monte Carlo Functions"
      ],
      "topics": [
        "DiffBetaMC"
      ]
    },
    {
      "page": "MC",
      "title": "Generate the Sampling Distribution of Regression Parameters Using the Monte Carlo Method",
      "concept": [
        "Beta Monte Carlo Functions"
      ],
      "topics": [
        "MC"
      ]
    },
    {
      "page": "MCMI",
      "title": "Generate the Sampling Distribution of Regression Parameters Using the Monte Carlo Method for Data with Missing Values",
      "concept": [
        "Beta Monte Carlo Functions"
      ],
      "topics": [
        "MCMI"
      ]
    },
    {
      "page": "nas1982",
      "title": "1982 National Academy of Sciences Doctoral Programs Data",
      "topics": [
        "nas1982"
      ]
    },
    {
      "page": "PCorMC",
      "title": "Estimate Squared Partial Correlation Coefficients and Generate the Corresponding Sampling Distribution Using the Monte Carlo Method",
      "concept": [
        "Beta Monte Carlo Functions"
      ],
      "topics": [
        "PCorMC"
      ]
    },
    {
      "page": "print.betamc",
      "title": "Print Method for an Object of Class 'betamc'",
      "topics": [
        "print.betamc"
      ]
    },
    {
      "page": "print.mc",
      "title": "Print Method for an Object of Class 'mc'",
      "topics": [
        "print.mc"
      ]
    },
    {
      "page": "RSqMC",
      "title": "Estimate Multiple Correlation Coefficients (R-Squared and Adjusted R-Squared) and Generate the Corresponding Sampling Distribution Using the Monte Carlo Method",
      "concept": [
        "Beta Monte Carlo Functions"
      ],
      "topics": [
        "RSqMC"
      ]
    },
    {
      "page": "SCorMC",
      "title": "Estimate Semipartial Correlation Coefficients and Generate the Corresponding Sampling Distribution Using the Monte Carlo Method",
      "concept": [
        "Beta Monte Carlo Functions"
      ],
      "topics": [
        "SCorMC"
      ]
    },
    {
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      "title": "Summary Method for an Object of Class 'betamc'",
      "topics": [
        "summary.betamc"
      ]
    },
    {
      "page": "summary.mc",
      "title": "Summary Method for an Object of Class 'mc'",
      "topics": [
        "summary.mc"
      ]
    },
    {
      "page": "vcov.betamc",
      "title": "Sampling Variance-Covariance Matrix Method for an Object of Class 'betamc'",
      "topics": [
        "vcov.betamc"
      ]
    }
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