{
  "_id": "6a101636acfb0bcc41c84529",
  "Package": "weights",
  "Title": "Weighting and Weighted Statistics",
  "Version": "1.1.2",
  "Date": "2025-06-18",
  "Authors@R": "c(person(given = \"Josh\",\nfamily = \"Pasek\",\nrole = c(\"aut\", \"cre\"),\nemail = \"josh@joshpasek.com\",\ncomment = c(ORCID = \"0000-0001-6099-6119\")),\nperson(given = \"Alex\",\nfamily = \"Tahk\",\nrole = c(\"ctb\"),\nemail = \"atahk@wisc.edu\",\ncomment = c(ORCID = \"0000-0001-7895-9420\")),\nperson(given=\"Gene\",\nfamily = \"Culter\",\nrole = c(\"ctb\"),\nemail = \"gcutler@amgen.com\"),\nperson(given = \"Marcus\",\nfamily = \"Schwemmle\",\nrole = c(\"ctb\"),\nemail=\"marcus.schwemmle@gfk.com\"),\nperson(given = c(\"Some\", \"code\", \"modified\", \"from\", \"R-core\"), family = \"\", role = \"ctb\"))",
  "Description": "Provides a variety of functions for producing simple\nweighted statistics, such as weighted Pearson's correlations,\npartial correlations, Chi-Squared statistics, histograms, and\nt-tests as well as simple weighting graphics including weighted\nhistograms, box plots, bar plots, and violin plots.  Also\nincludes software for quickly recoding survey data and plotting\nestimates from interaction terms in regressions (and multiply\nimputed regressions) both with and without weights and\nsummarizing various types of regressions. Some portions of this\npackage were assisted by AI-generated suggestions using\nOpenAI's GPT model, with human review and integration.",
  "License": "GPL (>= 2)",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-05-14 09:08:20 UTC",
    "User": "root"
  },
  "Author": "Josh Pasek [aut, cre] (ORCID:\n<https://orcid.org/0000-0001-6099-6119>), Alex Tahk [ctb]\n(ORCID: <https://orcid.org/0000-0001-7895-9420>), Gene Culter\n[ctb], Marcus Schwemmle [ctb], Some code modified from R-core\n[ctb]",
  "Maintainer": "Josh Pasek <josh@joshpasek.com>",
  "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev libx11-dev\nzlib1g-dev",
  "Repository": "https://jmping.r-universe.dev",
  "Date/Publication": "2025-06-18 16:10:02 UTC",
  "RemoteUrl": "https://github.com/cran/weights",
  "RemoteRef": "HEAD",
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  "MD5sum": "b4b6afa0b48874eed5143f653912a4f0",
  "_user": "jmping",
  "_type": "src",
  "_file": "weights_1.1.2.tar.gz",
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  "_created": "2026-05-14T09:08:20.000Z",
  "_published": "2026-05-22T08:39:18.044Z",
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    "author": "Josh Pasek <josh@joshpasek.com>",
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      "date": "2025-06-10"
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    "description": "Assoc. Prof @umich @umisrcps"
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  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/weights.html",
    "manual.pdf"
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  "_realowner": "jmping",
  "_cranurl": false,
  "_releases": [
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    },
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      "date": "2011-04-28"
    },
    {
      "version": "0.70",
      "date": "2011-08-16"
    },
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      "date": "2011-12-21"
    },
    {
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    },
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    },
    {
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      "date": "2014-03-04"
    },
    {
      "version": "0.85",
      "date": "2016-02-12"
    },
    {
      "version": "0.90",
      "date": "2018-04-27"
    },
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      "date": "2020-02-12"
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      "date": "2025-06-10"
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    "dummify",
    "findn",
    "findwtdinteraction",
    "findwtdinteraction.default",
    "findwtdinteraction.list",
    "findwtdinteraction.lmerMod",
    "findwtdinteraction.mira",
    "findwtdinteraction.multinom",
    "nalevs",
    "onetable",
    "plotinteractpreds",
    "plotinteractpreds.default",
    "plotinteractpreds.interactpreds",
    "plotinteractpreds.interactpredsmnl",
    "plotwtdinteraction",
    "rd",
    "starmaker",
    "stdz",
    "wpct",
    "wtd.anova",
    "wtd.barplot",
    "wtd.boxplot",
    "wtd.chi.sq",
    "wtd.cor",
    "wtd.cors",
    "wtd.cov",
    "wtd.hist",
    "wtd.median",
    "wtd.partial.cor",
    "wtd.partial.cov",
    "wtd.t.test",
    "wtd.violinplot",
    "wtd.xtab"
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      "name": "anes04",
      "title": "Demographic Data From 2004 American National Election Studies (ANES)",
      "object": "anes04",
      "class": [
        "data.frame"
      ],
      "fields": [
        "female",
        "age",
        "educcats",
        "racecats",
        "married"
      ],
      "rows": 1212,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "anes04",
      "title": "Demographic Data From 2004 American National Election Studies (ANES)",
      "topics": [
        "anes04"
      ]
    },
    {
      "page": "coeffer",
      "title": "Extract model coefficients with standard errors and significance stars",
      "topics": [
        "coeffer",
        "coeffer.default",
        "coeffer.gam",
        "coeffer.glmerMod",
        "coeffer.glmnet",
        "coeffer.lmerMod",
        "coeffer.multinom",
        "coeffer.polr"
      ]
    },
    {
      "page": "dummify",
      "title": "Separate a factor into separate dummy variables for each level.",
      "topics": [
        "dummify"
      ]
    },
    {
      "page": "findn",
      "title": "Summarize key model information including sample size and fit statistics",
      "topics": [
        "findn",
        "findn.default",
        "findn.gam",
        "findn.glm",
        "findn.glmerMod",
        "findn.lm",
        "findn.lmerMod",
        "findn.multinom",
        "findn.polr",
        "print.findn"
      ]
    },
    {
      "page": "nalevs",
      "title": "Recode variables to 0-1 scale",
      "topics": [
        "nalevs"
      ]
    },
    {
      "page": "onetable",
      "title": "Create a clean regression summary table from one or more models",
      "topics": [
        "onetable"
      ]
    },
    {
      "page": "plotwtdinteraction",
      "title": "Functions to Identify and Plot Predicted Probabilities As Well As Two- and Three-Way Interactions From Regressions With or Without Weights and Standard Errors",
      "topics": [
        "findwtdinteraction",
        "findwtdinteraction.default",
        "findwtdinteraction.list",
        "findwtdinteraction.lmerMod",
        "findwtdinteraction.mira",
        "findwtdinteraction.multinom",
        "plotinteractpreds",
        "plotinteractpreds.default",
        "plotinteractpreds.interactpreds",
        "plotinteractpreds.interactpredsmnl",
        "plotwtdinteraction"
      ]
    },
    {
      "page": "rd",
      "title": "Round Numbers To Text With No Leading Zero",
      "topics": [
        "rd"
      ]
    },
    {
      "page": "starmaker",
      "title": "Produce stars from p values for tables.",
      "topics": [
        "starmaker"
      ]
    },
    {
      "page": "stdz",
      "title": "Standardizes any numerical vector, with weights.",
      "topics": [
        "stdz"
      ]
    },
    {
      "page": "wpct",
      "title": "Provides a weighted table of percentages for any variable.",
      "topics": [
        "wpct"
      ]
    },
    {
      "page": "wtd.anova",
      "title": "Weighted one-way ANOVA",
      "topics": [
        "wtd.anova"
      ]
    },
    {
      "page": "wtd.barplot",
      "title": "Weighted barplot",
      "topics": [
        "wtd.barplot"
      ]
    },
    {
      "page": "wtd.boxplot",
      "title": "Weighted boxplot",
      "topics": [
        "wtd.boxplot"
      ]
    },
    {
      "page": "wtd.chi.sq",
      "title": "Produces weighted chi-squared tests.",
      "topics": [
        "wtd.chi.sq"
      ]
    },
    {
      "page": "wtd.cor",
      "title": "Produces weighted correlations with standard errors and significance. For a faster version without standard errors and p values, use the 'wtd.cors' function.",
      "topics": [
        "onecor.wtd",
        "wtd.cor"
      ]
    },
    {
      "page": "wtd.cors",
      "title": "Produces weighted correlations quickly using C.",
      "topics": [
        "wtd.cors"
      ]
    },
    {
      "page": "wtd.cov",
      "title": "Produces weighted covariances with standard errors and significance.",
      "topics": [
        "wtd.cov"
      ]
    },
    {
      "page": "wtd.hist",
      "title": "Weighted Histograms",
      "topics": [
        "wtd.hist"
      ]
    },
    {
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      "title": "Weighted median",
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    },
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    },
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      "title": "Computes weighted partial covariances, controlling for covariates",
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        "wtd.partial.cov"
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    },
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    },
    {
      "page": "wtd.violinplot",
      "title": "Draw weighted violin plots by group",
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      ]
    },
    {
      "page": "wtd.xtab",
      "title": "Weighted cross-tabulations using up to three categorical variables",
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      ]
    }
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