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  "Title": "Bootstrap Methods for Nested Linear Mixed-Effects Models",
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  "Authors@R": "c(person(\"Adam\", \"Loy\", email = \"loyad01@gmail.com\",\nrole = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-5780-4611\")),\nperson(\"Spenser\", \"Steele\", role = \"aut\"),\nperson(\"Jenna\", \"Korobova\", role = \"aut\"),\nperson(\"Ilmari\", \"Tamminen\", role = \"ctb\"))",
  "Description": "Bootstrap routines for nested linear mixed effects models\nfit using either 'lme4' or 'nlme'. The provided 'bootstrap()'\nfunction implements the parametric, residual, cases, random\neffect block (REB), and wild bootstrap procedures. An overview\nof these procedures can be found in Van der Leeden et al.\n(2008) <doi: 10.1007/978-0-387-73186-5_11>, Carpenter,\nGoldstein & Rasbash (2003) <doi: 10.1111/1467-9876.00415>, and\nChambers & Chandra (2013) <doi: 10.1080/10618600.2012.681216>.",
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  "Repository": "https://aloy.r-universe.dev",
  "Date/Publication": "2023-12-07 14:50:53 UTC",
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  "Author": "Adam Loy [aut, cre] (ORCID: <https://orcid.org/0000-0002-5780-4611>),\nSpenser Steele [aut],\nJenna Korobova [aut],\nIlmari Tamminen [ctb]",
  "Maintainer": "Adam Loy <loyad01@gmail.com>",
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    "extra/citation.json",
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    "extra/contents.json",
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      "date": "2016-07-14"
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    },
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    "reb_bootstrap",
    "resid_bootstrap",
    "wild_bootstrap"
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      "title": "Junior school project math score data.",
      "object": "jsp728",
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        "tbl",
        "data.frame"
      ],
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        "mathAge11",
        "mathAge8",
        "gender",
        "class",
        "school",
        "normAge11",
        "normAge8",
        "schoolMathAge8",
        "mathAge8c"
      ],
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      "table": true,
      "tojson": true
    }
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      "title": "Calculate Bootstrap p-values for fixed effects",
      "topics": [
        "bootstrap_pvals",
        "bootstrap_pvals.lme",
        "bootstrap_pvals.merMod"
      ]
    },
    {
      "page": "bootstrap",
      "title": "Bootstrap Nested Linear Mixed-Effects Models",
      "topics": [
        "bootstrap",
        "bootstrap.lme",
        "bootstrap.merMod"
      ]
    },
    {
      "page": "case_bootstrap",
      "title": "Cases Bootstrap for Nested LMEs",
      "topics": [
        "case_bootstrap",
        "case_bootstrap.lme",
        "case_bootstrap.merMod"
      ]
    },
    {
      "page": "combine",
      "title": "Combine bootstrap results",
      "topics": [
        "combine_lmeresamp"
      ]
    },
    {
      "page": "combine_pvals",
      "title": "Combine p-values",
      "topics": [
        "combine_pvals"
      ]
    },
    {
      "page": "confint",
      "title": "Calculate confidence intervals for a lmeresamp object",
      "topics": [
        "confint.lmeresamp"
      ]
    },
    {
      "page": "extract_parameters",
      "title": "Extract parameters from LME models",
      "topics": [
        "extract_parameters"
      ]
    },
    {
      "page": "jsp728",
      "title": "Junior school project math score data.",
      "topics": [
        "jsp728"
      ]
    },
    {
      "page": "lmeresampler",
      "title": "lmeresampler: A package for bootstrapping nested linear mixed-effects models",
      "topics": [
        "lmeresampler",
        "package-lmeresampler"
      ]
    },
    {
      "page": "parametric_bootstrap",
      "title": "Parametric Bootstrap for Nested LMEs",
      "topics": [
        "parametric_bootstrap",
        "parametric_bootstrap.lme",
        "parametric_bootstrap.merMod"
      ]
    },
    {
      "page": "plot",
      "title": "Plot bootstrap results",
      "topics": [
        "plot.lmeresamp"
      ]
    },
    {
      "page": "print.coef_tbl",
      "title": "Print coefficients from a 'coef_tbl' object",
      "topics": [
        "print.coef_tbl"
      ]
    },
    {
      "page": "print",
      "title": "Print a summary of an 'lmeresamp' object",
      "topics": [
        "print.lmeresamp"
      ]
    },
    {
      "page": "reb_bootstrap",
      "title": "REB Bootstrap for Two-Level Nested LMEs",
      "topics": [
        "reb_bootstrap",
        "reb_bootstrap.lme",
        "reb_bootstrap.lmerMod"
      ]
    },
    {
      "page": "resid_bootstrap",
      "title": "Residual Bootstrap for Nested LMEs",
      "topics": [
        "resid_bootstrap",
        "resid_bootstrap.lme",
        "resid_bootstrap.merMod"
      ]
    },
    {
      "page": "summary",
      "title": "Calculate summary statistics for 'lmeresamp' objects",
      "topics": [
        "summary.lmeresamp"
      ]
    },
    {
      "page": "wild_bootstrap",
      "title": "Wild Bootstrap for LME models",
      "topics": [
        "wild_bootstrap",
        "wild_bootstrap.lme",
        "wild_bootstrap.lmerMod"
      ]
    }
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      "title": "Vignette",
      "engine": "knitr::rmarkdown_notangle",
      "headings": [
        "Overview",
        "The Data",
        "The Call",
        "1. The Parametric Bootstrap",
        "Examples",
        "bootstrap() output",
        "2. The Cases Bootstrap",
        "3. The Residual Bootstrap",
        "4. The Wild Bootstrap",
        "5. The Random Effects Block (REB) Bootstrap",
        "6. Output Options",
        "The summary() function",
        "Example",
        "The print() Function",
        "The confint() Function",
        "The plot() function",
        "7. Bootstrapping with GLMMs",
        "8. Parallelization (User Extension)",
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        "Performance",
        "Implementation",
        "9. Future Directions (Developer Extensions)",
        "References"
      ],
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      "modified": "2022-03-24 21:49:24",
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