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  "Package": "LikertMakeR",
  "Title": "Synthesise and Correlate Likert Scale and Rating-Scale Data\nBased on Summary Statistics",
  "Version": "2.3.0",
  "Date": "2026-04-28",
  "Authors@R": "person(\"Hume\", \"Winzar\", , \"winzar@gmail.com\", role = c(\"cre\", \"aut\"),\ncomment = c(ORCID = \"0000-0001-7475-2641\"))",
  "Description": "Generate and correlate synthetic Likert and rating-scale\nquestionnaire responses with predefined means, standard\ndeviations, Cronbach's Alpha, Factor Loading table,\ncoefficients, and other summary statistics. It can be used to\nsimulate Likert data, construct multi-item scales, generate\ncorrelation matrices, and create example survey datasets for\nteaching statistics, psychometrics, and methodological\nresearch. Worked examples and documentation are available in\nthe package articles, accessible via the package website,\n<https://winzarh.github.io/LikertMakeR/>.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/WinzarH/LikertMakeR/,\nhttps://winzarh.github.io/LikertMakeR/,\nhttps://github.com/WinzarH/LikertMakeR",
  "BugReports": "https://github.com/WinzarH/LikertMakeR/issues",
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  "Repository": "https://winzarh.r-universe.dev",
  "Date/Publication": "2026-06-05 08:44:59 UTC",
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  "Author": "Hume Winzar [cre, aut] (ORCID: <https://orcid.org/0000-0001-7475-2641>)",
  "Maintainer": "Hume Winzar <winzar@gmail.com>",
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    "eigenvalues",
    "lcor",
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    "lfast",
    "makeCorrAlpha",
    "makeCorrLoadings",
    "makeItemsScale",
    "makePaired",
    "makeRepeated",
    "makeScales",
    "makeScalesRegression",
    "ordinal_diagnostics",
    "reliability"
  ],
  "_help": [
    {
      "page": "alpha",
      "title": "Calculate Cronbach's Alpha from a correlation matrix or dataframe",
      "topics": [
        "alpha"
      ]
    },
    {
      "page": "alpha_sensitivity",
      "title": "Sensitivity of Cronbach's alpha to scale design parameters",
      "topics": [
        "alpha_sensitivity"
      ]
    },
    {
      "page": "correlateScales",
      "title": "Dataframe of correlated scales from different dataframes of scale items",
      "topics": [
        "correlateScales"
      ]
    },
    {
      "page": "eigenvalues",
      "title": "calculate eigenvalues of a correlation matrix with optional scree plot",
      "topics": [
        "eigenvalues"
      ]
    },
    {
      "page": "lcor",
      "title": "Rearrange elements in each column of a data-frame to fit a predefined correlation matrix",
      "topics": [
        "lcor"
      ]
    },
    {
      "page": "lexact",
      "title": "Deprecated. Use lfast() instead",
      "topics": [
        "lexact"
      ]
    },
    {
      "page": "lfast",
      "title": "Synthesise rating-scale data with predefined mean and standard deviation",
      "topics": [
        "lfast"
      ]
    },
    {
      "page": "makeCorrAlpha",
      "title": "Correlation matrix from Cronbach's Alpha",
      "topics": [
        "makeCorrAlpha"
      ]
    },
    {
      "page": "makeCorrLoadings",
      "title": "Generate Inter-Item Correlation Matrix from Factor Loadings",
      "topics": [
        "makeCorrLoadings"
      ]
    },
    {
      "page": "makeItemsScale",
      "title": "Generate scale items from a summated scale, with desired Cronbach's Alpha",
      "topics": [
        "makeItemsScale"
      ]
    },
    {
      "page": "makePaired",
      "title": "Synthesise a dataset from paired-sample t-test summary statistics",
      "topics": [
        "makePaired"
      ]
    },
    {
      "page": "makeRepeated",
      "title": "Reproduce Repeated-Measures Data from ANOVA Summary Statistics",
      "topics": [
        "makeRepeated"
      ]
    },
    {
      "page": "makeScales",
      "title": "Synthesise rating-scale data with given first and second moments and a predefined correlation matrix",
      "topics": [
        "makeScales"
      ]
    },
    {
      "page": "makeScalesRegression",
      "title": "Generate Data from Multiple-Regression Summary Statistics",
      "topics": [
        "makeScalesRegression"
      ]
    },
    {
      "page": "ordinal_diagnostics",
      "title": "Extract ordinal diagnostics from a reliability() result",
      "topics": [
        "ordinal_diagnostics"
      ]
    },
    {
      "page": "reliability",
      "title": "Estimate scale reliability for Likert and rating-scale data",
      "topics": [
        "reliability"
      ]
    }
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  "_readme": "https://github.com/winzarh/likertmaker/raw/HEAD/README.md",
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      "source": "LikertMakeR_vignette.Rmd",
      "filename": "LikertMakeR_vignette.html",
      "title": "LikertMakeR vignette",
      "author": "Hume Winzar",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Purpose",
        "Motivation",
        "Rating scale properties",
        "Rating scales have bounds and discrete measurement intervals",
        "A single 1-5 rating scale is NOT a Likert scale - it may be an Likert-scale item.",
        "Most rating scales are skewed",
        "LikertMakeR functions",
        "Using LikertMakeR",
        "Download and Install LikertMakeR",
        "from CRAN",
        "development version from GitHub.",
        "Generate synthetic rating-scale data",
        "lfast()",
        "lfast() example",
        "a four-item, five-point Likert scale",
        "an 11-point likelihood-of-purchase scale",
        "Correlating rating scales",
        "lcor()",
        "lcor() example",
        "Generate a correlation matrix from Cronbach's Alpha",
        "makeCorrAlpha()",
        "makeCorrAlpha() examples",
        "Four variables, alpha = 0.85",
        "test output with Helper functions",
        "makeCorrAlpha() with diagnostics output",
        "diagnostics output",
        "Generate a correlation matrix from factor loadings",
        "makeCorrLoadings",
        "makeCorrLoadings() usage",
        "makeCorrLoadings() arguments",
        "Note",
        "makeCorrLoadings() examples",
        "Typical application from published EFA results",
        "define parameters",
        "Apply the function",
        "Test makeCorrLoadings() output",
        "Assuming orthogonal factors",
        "Test orthogonal output",
        "Generate a dataframe of rating scales from a correlation matrix and predefined moments",
        "makeScales()",
        "makeScales() examples",
        "makeScales() example #1. four correlated items",
        "Structure of new dataframe",
        "Means should be correct to two decimal places",
        "Correlations should be correct to two decimal places",
        "makeScales() example #2. four Likert scales",
        "Generate a dataframe from Cronbach's Alpha and predefined moments",
        "Step 1: Generate a correlation matrix",
        "Step 2: Generate dataframe",
        "Summary plots of new dataframe",
        "Generate a dataframe of rating-scale items from a summated rating scale",
        "makeItemsScale()",
        "makeItemsScale() Example:",
        "create items with makeItemsScale()",
        "makeItemsScale() with same summated values and higher alpha",
        "Create a dataframe for a t-test",
        "Independent-samples t-test",
        "makePaired() paired-sample t-test",
        "makePaired() examples",
        "check properties of new data",
        "run a paired-sample t-test with the new data",
        "Create a dataframe for Repeated-Measures ANOVA",
        "makeRepeated()",
        "makeRepeated() usage",
        "makeRepeated() arguments",
        "makeRepeated() examples",
        "Generate rating-scale data from multiple regression results",
        "makeScalesRegression()",
        "makeScalesRegression() usage",
        "makeScalesRegression() arguments",
        "makeScalesRegression() examples",
        "Example 1: With provided IV correlation matrix",
        "Example 2: With optimisation (no IV correlation matrix)",
        "Create a multidimensional dataframe of correlated scale items",
        "correlateScales()",
        "correlateScales() examples",
        "three attitudes and a behavioural intention",
        "create dataframes of Likert-scale items",
        "check properties of item dataframes",
        "correlateScales parameters",
        "apply the correlateScales() function",
        "plot the new correlated scale items",
        "Check the properties of our derived dataframe",
        "Helper functions",
        "alpha()",
        "alpha() examples",
        "eigenvalues()",
        "eigenvalues() examples",
        "eigenvalues() function with optional scree plot",
        "reliability()",
        "reliability() examples",
        "Alternative methods & packages",
        "sampling from a truncated normal distribution",
        "sampling with a predetermined probability distribution",
        "marginal model specification",
        "Factor Models: Classical Test Theory (CTT)",
        "References"
      ],
      "created": "2025-05-27 12:07:00",
      "modified": "2026-05-21 03:12:06",
      "commits": 22
    },
    {
      "source": "reliability_measures.Rmd",
      "filename": "reliability_measures.html",
      "title": "likertMakeR::reliability()",
      "author": "Hume Winzar",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Reliability estimation with LikertMakeR::reliability()",
        "When should you use reliability()?",
        "Function usage",
        "Arguments",
        "data",
        "include",
        "ci",
        "ci_level",
        "n_boot",
        "na_method",
        "min_count",
        "digits",
        "verbose",
        "Reliability coefficients returned",
        "Pearson-based coefficients (always available)",
        "Ordinal (polychoric-based) coefficients",
        "Ordinal diagnostics and safeguards",
        "Hierarchical reliability: $\\omega_h$ (Coefficient H)",
        "Why no confidence intervals for $\\omega_h$?",
        "Examples",
        "Create a synthetic dataset",
        "Basic reliability estimates",
        "Including additional coefficients",
        "When should I use each option?",
        "Notes on computation",
        "Choosing a Reliability Coefficient: A Practical Decision Guide",
        "Step 1: What kind of data do you have?",
        "Continuous or approximately continuous items",
        "Ordinal (Likert-type) items",
        "Step 2: Choosing between $\\alpha$ and $\\omega$",
        "Cronbach’s alpha ($\\alpha$)",
        "McDonald’s omega ($\\omega$)",
        "Where does Guttman’s $\\lambda_6$ fit?",
        "Step 3: When should I use ordinal reliability?",
        "Step 4: $\\alpha$ vs $\\omega$ vs ordinal $\\omega$ — a practical summary",
        "Step 5: Confidence intervals",
        "Recommended reading",
        "Understanding Cronbach’s alpha and its limitations",
        "Omega and factor-based reliability",
        "Comparative studies",
        "Ordinal reliability for Likert-type data",
        "Polychoric correlations in practice",
        "Teaching tip",
        "Citations"
      ],
      "created": "2025-12-31 06:51:33",
      "modified": "2026-03-21 09:56:18",
      "commits": 2
    }
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