{
  "_id": "6a1d490d1d7bb097a0a42c18",
  "Package": "r2glmm",
  "Type": "Package",
  "Title": "Computes R Squared for Mixed (Multilevel) Models",
  "Date": "2025-04-28",
  "Version": "0.1.3",
  "Authors@R": "person(\"Byron\", \"Jaeger\", email = \"byron.jaeger@gmail.com\", role = c(\"aut\", \"cre\"))",
  "Description": "The model R squared and semi-partial R squared for the\nlinear and generalized linear mixed model (LMM and GLMM) are\ncomputed with confidence limits. The R squared measure from\nEdwards et.al (2008) <DOI:10.1002/sim.3429> is extended to the\nGLMM using penalized quasi-likelihood (PQL) estimation (see\nJaeger et al. 2016 <DOI:10.1080/02664763.2016.1193725>). Three\nmethods of computation are provided and described as follows.\nFirst, The Kenward-Roger approach. Due to some inconsistency\nbetween the 'pbkrtest' package and the 'glmmPQL' function, the\nKenward-Roger approach in the 'r2glmm' package is limited to\nthe LMM. Second, The method introduced by Nakagawa and\nSchielzeth (2013) <DOI:10.1111/j.2041-210x.2012.00261.x> and\nlater extended by Johnson (2014) <DOI:10.1111/2041-210X.12225>.\nThe 'r2glmm' package only computes marginal R squared for the\nLMM and does not generalize the statistic to the GLMM; however,\nconfidence limits and semi-partial R squared for fixed effects\nare useful additions. Lastly, an approach using standardized\ngeneralized variance (SGV) can be used for covariance model\nselection. Package installation instructions can be found in\nthe readme file.",
  "License": "GPL-2",
  "RoxygenNote": "7.3.2",
  "URL": "https://github.com/bcjaeger/r2glmm",
  "BugReports": "https://github.com/bcjaeger/r2glmm/issues",
  "Config/pak/sysreqs": "cmake make libicu-dev",
  "Repository": "https://bcjaeger.r-universe.dev",
  "Date/Publication": "2025-04-28 14:02:50 UTC",
  "RemoteUrl": "https://github.com/bcjaeger/r2glmm",
  "RemoteRef": "HEAD",
  "RemoteSha": "f19be6656fbf38d31539a8e93d09d31d27890476",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-01 08:50:23 UTC",
    "User": "root"
  },
  "Author": "Byron Jaeger [aut, cre]",
  "Maintainer": "Byron Jaeger <byron.jaeger@gmail.com>",
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  "_created": "2026-06-01T08:50:23.000Z",
  "_published": "2026-06-01T08:55:41.177Z",
  "_distro": "noble",
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    "author": "Byron Jaeger <bcjaeger@perisphere-rwe.com>",
    "committer": "Byron Jaeger <bcjaeger@perisphere-rwe.com>",
    "message": "update date\n",
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    "email": "byron.jaeger@gmail.com",
    "login": "bcjaeger",
    "description": "Director of Data Analytics at Perisphere Real World Evidence",
    "uuid": 11821781
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  "_dependencies": [
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      "role": "Imports"
    },
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      "role": "Imports"
    },
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      "role": "Imports"
    },
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      "role": "Suggests"
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    },
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  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_stars": 16,
  "_contributors": [
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      "count": 47,
      "uuid": 11821781
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  "_userbio": {
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    "type": "user",
    "name": "Byron",
    "description": "Director of Data Analytics at Perisphere Real World Evidence"
  },
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/r2glmm"
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  "_mentions": 40,
  "_devurl": "https://github.com/bcjaeger/r2glmm",
  "_searchresults": 291,
  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/r2glmm.html",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
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  "_homeurl": "https://github.com/bcjaeger/r2glmm",
  "_realowner": "bcjaeger",
  "_cranurl": true,
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      "date": "2016-09-15"
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    "calc_sgv",
    "cmp_R2",
    "glmPQL",
    "is.CompSym",
    "make.partial.C",
    "pqlmer",
    "r2beta",
    "r2dt"
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  "_help": [
    {
      "page": "calc_sgv",
      "title": "Compute the standardized generalized variance (SGV) of a blocked diagonal matrix.",
      "topics": [
        "calc_sgv"
      ]
    },
    {
      "page": "cmp_R2",
      "title": "Compute R2 with a specified C matrix",
      "topics": [
        "cmp_R2"
      ]
    },
    {
      "page": "glmPQL",
      "title": "Compute PQL estimates for fixed effects from a generalized linear model.",
      "topics": [
        "glmPQL"
      ]
    },
    {
      "page": "is.CompSym",
      "title": "Checks if a matrix is Compound Symmetric.",
      "topics": [
        "is.CompSym"
      ]
    },
    {
      "page": "make.partial.C",
      "title": "Generate partial contrast matrices",
      "topics": [
        "make.partial.C"
      ]
    },
    {
      "page": "plot.R2",
      "title": "Visualize standardized effect sizes and model R squared",
      "topics": [
        "plot.R2"
      ]
    },
    {
      "page": "pqlmer",
      "title": "pqlmer",
      "topics": [
        "pqlmer"
      ]
    },
    {
      "page": "print.R2",
      "title": "Print the contents of an R2 object",
      "topics": [
        "print.R2"
      ]
    },
    {
      "page": "r2beta",
      "title": "r2beta Compute R Squared for Mixed Models",
      "topics": [
        "r2beta"
      ]
    },
    {
      "page": "r2dt",
      "title": "R Squared Difference Test (R2DT). Test for a statistically significant difference in generalized explained variance between two candidate models.",
      "topics": [
        "r2dt"
      ]
    }
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