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  "Package": "rockchalk",
  "Type": "Package",
  "Title": "Regression Estimation and Presentation",
  "Version": "1.8.164",
  "Date": "2026-04-15",
  "Authors@R": "c(person(\"Paul E.\",\"Johnson\",email=\"pauljohn32@freefaculty.org\",role = c(\"aut\", \"cre\")),\nperson(\"Gabor\", \"Grothendieck\",email=\"ggrothendieck@gmail.com\", role=\"ctb\"),\nperson(\"Dimitri\", \"Papadopoulos OrfanosGabor\", email=\"dimitri.papadopoulos@cea.fr\", role=\"ctb\"))",
  "Maintainer": "Paul E. Johnson <pauljohn32@freefaculty.org>",
  "Description": "A collection of functions for interpretation and\npresentation of regression analysis.  These functions are used\nto produce the statistics lectures in\n<https://pj.freefaculty.org/guides/>. Includes regression\ndiagnostics, regression tables, and plots of interactions and\n\"moderator\" variables. The emphasis is on \"mean-centered\" and\n\"residual-centered\" predictors. The vignette 'rockchalk' offers\na fairly comprehensive overview.  The vignette 'Rstyle' has\nadvice about coding in R.  The package title 'rockchalk' refers\nto our school motto, 'Rock Chalk Jayhawk, Go K.U.'.",
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  "Author": "Paul E. Johnson [aut, cre], Gabor Grothendieck [ctb], Dimitri\nPapadopoulos OrfanosGabor [ctb]",
  "Config/pak/sysreqs": "cmake make libicu-dev",
  "Repository": "https://pauljohn32.r-universe.dev",
  "Date/Publication": "2026-04-16 08:10:03 UTC",
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    "drawnorm",
    "focalVals",
    "formatSummarizedFactors",
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    "genCorrelatedData3",
    "genX",
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    "getFocal",
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    "gmc",
    "kurtosis",
    "lazyCor",
    "lazyCov",
    "lmAuxiliary",
    "magRange",
    "makeSymmetric",
    "mcDiagnose",
    "mcGraph1",
    "mcGraph2",
    "mcGraph3",
    "meanCenter",
    "model.data",
    "mvrnorm",
    "newdata",
    "outreg",
    "outreg2HTML",
    "padW0",
    "pctable",
    "perspEmpty",
    "plotCurves",
    "plotPlane",
    "plotSeq",
    "plotSlopes",
    "predictOMatic",
    "rbindFill",
    "removeNULL",
    "residualCenter",
    "skewness",
    "standardize",
    "summarize",
    "summarizeFactors",
    "summarizeNumerics",
    "testSlopes",
    "vech2Corr",
    "vech2mat",
    "waldt"
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      "file": "cheating.RData",
      "class": [
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        "dist",
        "year",
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        "jiban",
        "cheating",
        "looting",
        "actualratio",
        "viab",
        "inc",
        "cons",
        "ur",
        "newcand",
        "jwins",
        "cons_cwins",
        "oth_cwins",
        "camp",
        "fleader",
        "incablast",
        "predratio",
        "m",
        "candcamp",
        "candothercamp",
        "kunocheat",
        "kunoloot"
      ],
      "rows": 16623,
      "table": true,
      "tojson": true
    },
    {
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      "title": "Religious beliefs and crime rates",
      "object": "religioncrime",
      "file": "religioncrime.RData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "heaven",
        "hell",
        "crime"
      ],
      "rows": 51,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "rockchalk-package",
      "title": "rockchalk: regression functions",
      "topics": [
        "rockchalk-package",
        "rockchalk"
      ]
    },
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      "title": "Superimpose regression lines on a plotted plane",
      "topics": [
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      ]
    },
    {
      "page": "centerNumerics",
      "title": "Find numeric columns, center them, re-name them, and join them with the original data.",
      "topics": [
        "centerNumerics"
      ]
    },
    {
      "page": "centralValues",
      "title": "Central Tendency estimates for variables",
      "topics": [
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      ]
    },
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      "title": "A way of checking if a string is a valid file name.",
      "topics": [
        "checkIntFormat"
      ]
    },
    {
      "page": "checkPosDef",
      "title": "Check a matrix for positive definitness",
      "topics": [
        "checkPosDef"
      ]
    },
    {
      "page": "combineLevels",
      "title": "recode a factor by \"combining\" levels",
      "topics": [
        "combineLevels"
      ]
    },
    {
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      "title": "Calculates the \"center\" quantiles, always including the median, when n is odd.",
      "topics": [
        "cutByQuantile"
      ]
    },
    {
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      "title": "Returns center values of x, the mean, mean-std.dev, mean+std.dev",
      "topics": [
        "cutBySD"
      ]
    },
    {
      "page": "cutByTable",
      "title": "Select most frequently occurring values from numeric or categorical variables.",
      "topics": [
        "cutByTable"
      ]
    },
    {
      "page": "cutFancy",
      "title": "Create an ordinal variable by grouping numeric data input.",
      "topics": [
        "cutFancy"
      ]
    },
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      "title": "Summary stats table-maker for regression users",
      "topics": [
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      ]
    },
    {
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      "title": "Create a uniquely named directory. Appends number & optionally date to directory name.",
      "topics": [
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      ]
    },
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      "title": "draw a normal distribution with beautiful illustrations",
      "topics": [
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      ]
    },
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      "title": "Create a focal value vector.",
      "topics": [
        "focalVals"
      ]
    },
    {
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      "title": "Prints out the contents of an object created by summarizeFactors in the style of base::summary",
      "topics": [
        "formatSummarizedFactors"
      ]
    },
    {
      "page": "formatSummarizedNumerics",
      "title": "Reformat numeric summarize output as one column per variable, similar to R summary",
      "topics": [
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      ]
    },
    {
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      "title": "Generates a data frame for regression analysis",
      "topics": [
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      ]
    },
    {
      "page": "genCorrelatedData2",
      "title": "Generates a data frame for regression analysis.",
      "topics": [
        "genCorrelatedData2"
      ]
    },
    {
      "page": "genCorrelatedData3",
      "title": "Generate correlated data for simulations (third edition)",
      "topics": [
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      ]
    },
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      "title": "Generate correlated data (predictors) for one unit",
      "topics": [
        "genX"
      ]
    },
    {
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      "title": "retrieves estimates of the coefficient of determination from a list of regressions",
      "topics": [
        "getAuxRsq"
      ]
    },
    {
      "page": "getDeltaRsquare",
      "title": "Calculates the delta R-squares, also known as squared semi-partial correlation coefficients.",
      "topics": [
        "getDeltaRsquare"
      ]
    },
    {
      "page": "getFocal",
      "title": "Select focal values from an observed variable.",
      "topics": [
        "getFocal",
        "getFocal.character",
        "getFocal.default",
        "getFocal.factor"
      ]
    },
    {
      "page": "getPartialCor",
      "title": "Calculates partial correlation coefficients after retrieving data matrix froma fitted regression model",
      "topics": [
        "getPartialCor"
      ]
    },
    {
      "page": "getVIF",
      "title": "Converts the R-square to the variance inflation factor",
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        "getVIF"
      ]
    },
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      "title": "Group Mean Center: Generate group summaries and individual deviations within groups",
      "topics": [
        "gmc"
      ]
    },
    {
      "page": "kurtosis",
      "title": "Calculate excess kurtosis",
      "topics": [
        "kurtosis"
      ]
    },
    {
      "page": "lazyCor",
      "title": "Create correlation matrices.",
      "topics": [
        "lazyCor"
      ]
    },
    {
      "page": "lazyCov",
      "title": "Create covariance matrix from correlation and standard deviation information",
      "topics": [
        "lazyCov"
      ]
    },
    {
      "page": "lmAuxiliary",
      "title": "Estimate leave-one-variable-out regressions",
      "topics": [
        "lmAuxiliary"
      ]
    },
    {
      "page": "magRange",
      "title": "magRange Magnify the range of a variable.",
      "topics": [
        "magRange"
      ]
    },
    {
      "page": "makeSymmetric",
      "title": "Create Symmetric Matrices, possibly covariance or correlation matrices, or check a matrix for symmetry and serviceability.",
      "topics": [
        "makeSymmetric"
      ]
    },
    {
      "page": "makeVec",
      "title": "makeVec for checking or creating vectors",
      "topics": [
        "makeVec"
      ]
    },
    {
      "page": "mcDiagnose",
      "title": "Multi-collinearity diagnostics",
      "topics": [
        "mcDiagnose"
      ]
    },
    {
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      "title": "Illustrate multicollinearity in regression, part 1.",
      "topics": [
        "mcGraph1",
        "mcGraph2",
        "mcGraph3"
      ]
    },
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      "page": "meanCenter",
      "title": "meanCenter",
      "topics": [
        "meanCenter",
        "meanCenter.default"
      ]
    },
    {
      "page": "model.data",
      "title": "Create a \"raw\" (UNTRANSFORMED) data frame equivalent to the input data that would be required to fit the given model.",
      "topics": [
        "model.data"
      ]
    },
    {
      "page": "model.data.default",
      "title": "Create a data frame suitable for estimating a model",
      "topics": [
        "model.data.default"
      ]
    },
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      "title": "Minor revision of mvrnorm (from 'MASS') to facilitate replication",
      "topics": [
        "mvrnorm"
      ]
    },
    {
      "page": "newdata",
      "title": "Create a newdata frame for usage in predict methods",
      "topics": [
        "newdata",
        "newdata.default"
      ]
    },
    {
      "page": "outreg",
      "title": "Creates a publication quality result table for regression models. Works with models fitted with lm, glm, as well as lme4.",
      "topics": [
        "outreg"
      ]
    },
    {
      "page": "outreg2HTML",
      "title": "Convert LaTeX output from outreg to HTML markup",
      "topics": [
        "outreg2HTML"
      ]
    },
    {
      "page": "padW0",
      "title": "Pad with 0's.",
      "topics": [
        "padW0"
      ]
    },
    {
      "page": "pctable",
      "title": "Creates a cross tabulation with counts and percentages",
      "topics": [
        "pctable",
        "pctable.character",
        "pctable.default",
        "pctable.formula"
      ]
    },
    {
      "page": "perspEmpty",
      "title": "perspEmpty",
      "topics": [
        "perspEmpty"
      ]
    },
    {
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      "title": "Plot testSlopes objects",
      "topics": [
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      ]
    },
    {
      "page": "plotCurves",
      "title": "Assists creation of predicted value curves for regression models.",
      "topics": [
        "plotCurves"
      ]
    },
    {
      "page": "plotFancy",
      "title": "Regression plots with predicted value lines, confidence intervals, color coded interactions",
      "topics": [
        "plotFancy"
      ]
    },
    {
      "page": "plotFancyCategories",
      "title": "Draw display for discrete predictor in plotSlopes",
      "topics": [
        "plotFancyCategories"
      ]
    },
    {
      "page": "plotPlane",
      "title": "Draw a 3-D regression plot for two predictors from any linear or nonlinear lm or glm object",
      "topics": [
        "plotPlane",
        "plotPlane.default"
      ]
    },
    {
      "page": "plotSeq",
      "title": "Create sequences for plotting",
      "topics": [
        "plotSeq"
      ]
    },
    {
      "page": "plotSlopes",
      "title": "Generic function for plotting regressions and interaction effects",
      "topics": [
        "plotSlopes",
        "plotSlopes.lm"
      ]
    },
    {
      "page": "predictCI",
      "title": "Calculate a predicted value matrix (fit, lwr, upr) for a regression, either lm or glm, on either link or response scale.",
      "topics": [
        "predictCI"
      ]
    },
    {
      "page": "predictOMatic",
      "title": "Create predicted values after choosing values of predictors.  Can demonstrate marginal effects of the predictor variables.",
      "topics": [
        "predictOMatic"
      ]
    },
    {
      "page": "print.pctable",
      "title": "Display pctable objects",
      "topics": [
        "print.pctable"
      ]
    },
    {
      "page": "print.summarize",
      "title": "print method for output from summarize",
      "topics": [
        "print.summarize"
      ]
    },
    {
      "page": "print.summary.pctable",
      "title": "print method for summary.pctable objects",
      "topics": [
        "print.summary.pctable"
      ]
    },
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