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  "Title": "High-Level Functions for Tabulating, Charting and Reporting\nSurvey Data",
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  "Date": "2026-02-07",
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  "Description": "Craft polished tables and plots in Markdown reports.\nSimply choose whether to treat your data as counts or metrics,\nand the package will automatically generate well-designed\ndefault tables and plots for you. Boiled down to the basics,\nwith labeling features and simple interactive reports. All\nfunctions are 'tidyverse' compatible.",
  "URL": "https://github.com/strohne/volker,\nhttps://strohne.github.io/volker/",
  "BugReports": "https://github.com/strohne/volker/issues",
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  "Repository": "https://strohne.r-universe.dev",
  "Date/Publication": "2026-05-29 08:59:41 UTC",
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    "add_clusters",
    "add_factors",
    "add_index",
    "add_model",
    "agree_tab",
    "cluster_plot",
    "cluster_tab",
    "codebook",
    "data_clean",
    "data_clean_default",
    "data_prepare",
    "diagnostics_cooksd",
    "diagnostics_qq",
    "diagnostics_resid_fitted",
    "diagnostics_scale_location",
    "effect_counts",
    "effect_counts_items",
    "effect_counts_items_grouped",
    "effect_counts_items_grouped_items",
    "effect_counts_one",
    "effect_counts_one_grouped",
    "effect_metrics",
    "effect_metrics_items",
    "effect_metrics_items_cor",
    "effect_metrics_items_cor_items",
    "effect_metrics_items_grouped",
    "effect_metrics_one",
    "effect_metrics_one_cor",
    "effect_metrics_one_grouped",
    "ends_with",
    "factor_plot",
    "factor_tab",
    "filter",
    "html_report",
    "idx_add",
    "labs_apply",
    "labs_clear",
    "labs_restore",
    "labs_store",
    "model_metrics_plot",
    "model_metrics_tab",
    "model_plot",
    "model_tab",
    "mutate",
    "pdf_report",
    "plot_counts",
    "plot_counts_items",
    "plot_counts_items_cor",
    "plot_counts_items_grouped",
    "plot_counts_items_grouped_items",
    "plot_counts_one",
    "plot_counts_one_cor",
    "plot_counts_one_grouped",
    "plot_metrics",
    "plot_metrics_items",
    "plot_metrics_items_cor",
    "plot_metrics_items_cor_items",
    "plot_metrics_items_grouped",
    "plot_metrics_one",
    "plot_metrics_one_cor",
    "plot_metrics_one_grouped",
    "report_counts",
    "report_metrics",
    "select",
    "skim_metrics",
    "starts_with",
    "tab_counts",
    "tab_counts_items",
    "tab_counts_items_cor",
    "tab_counts_items_grouped",
    "tab_counts_one",
    "tab_counts_one_cor",
    "tab_counts_one_grouped",
    "tab_metrics",
    "tab_metrics_items",
    "tab_metrics_items_cor",
    "tab_metrics_items_cor_items",
    "tab_metrics_items_grouped",
    "tab_metrics_one",
    "tab_metrics_one_cor",
    "tab_metrics_one_grouped",
    "theme_set",
    "theme_vlkr",
    "tibble",
    "tribble"
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      "title": "ChatGPT Adoption Dataset CG-GE-APR23",
      "object": "chatgpt",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
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        "case",
        "use_private",
        "use_work",
        "cg_adoption_advantage_01",
        "cg_adoption_advantage_02",
        "cg_adoption_advantage_03",
        "cg_adoption_advantage_04",
        "cg_adoption_fearofuse_01",
        "cg_adoption_fearofuse_02",
        "cg_adoption_fearofuse_03",
        "cg_adoption_fearofuse_04",
        "cg_adoption_social_01",
        "cg_adoption_social_02",
        "cg_adoption_social_03",
        "cg_adoption_social_04",
        "adopter",
        "sd_age",
        "sd_gender",
        "cg_activities",
        "cg_act_write",
        "cg_act_test",
        "cg_act_search"
      ],
      "rows": 101,
      "table": true,
      "tojson": true
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      "page": "add_clusters",
      "title": "Add cluster number to a data frame",
      "topics": [
        "add_clusters"
      ]
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    {
      "page": "add_factors",
      "title": "Add PCA columns along with summary statistics (KMO and Bartlett test) to a data frame",
      "topics": [
        "add_factors"
      ]
    },
    {
      "page": "add_index",
      "title": "Calculate the mean value of multiple items",
      "topics": [
        "add_index"
      ]
    },
    {
      "page": "chatgpt",
      "title": "ChatGPT Adoption Dataset CG-GE-APR23",
      "topics": [
        "chatgpt"
      ]
    },
    {
      "page": "codebook",
      "title": "Get variable and value labels from a data set",
      "topics": [
        "codebook"
      ]
    },
    {
      "page": "effect_counts",
      "title": "Output effect sizes and test statistics for count data",
      "topics": [
        "effect_counts"
      ]
    },
    {
      "page": "effect_metrics",
      "title": "Output effect sizes and test statistics for metric data",
      "topics": [
        "effect_metrics"
      ]
    },
    {
      "page": "html_report",
      "title": "Volker style HTML document format",
      "topics": [
        "html_report"
      ]
    },
    {
      "page": "labs_apply",
      "title": "Set column and value labels",
      "topics": [
        "labs_apply"
      ]
    },
    {
      "page": "labs_clear",
      "title": "Remove all comments from the selected columns",
      "topics": [
        "labs_clear"
      ]
    },
    {
      "page": "labs_restore",
      "title": "Restore labels from the codebook store in the codebook attribute.",
      "topics": [
        "labs_restore"
      ]
    },
    {
      "page": "labs_store",
      "title": "Get the current codebook and store it in the codebook attribute.",
      "topics": [
        "labs_store"
      ]
    },
    {
      "page": "pdf_report",
      "title": "Volker style PDF document format",
      "topics": [
        "pdf_report"
      ]
    },
    {
      "page": "plot_counts",
      "title": "Output a frequency plot",
      "topics": [
        "plot_counts"
      ]
    },
    {
      "page": "plot_metrics",
      "title": "Output a plot with distribution parameters such as the mean values",
      "topics": [
        "plot_metrics"
      ]
    },
    {
      "page": "report_counts",
      "title": "Create table and plot for categorical variables",
      "topics": [
        "report_counts"
      ]
    },
    {
      "page": "report_metrics",
      "title": "Create table and plot for metric variables",
      "topics": [
        "report_metrics"
      ]
    },
    {
      "page": "tab_counts",
      "title": "Output a frequency table",
      "topics": [
        "tab_counts"
      ]
    },
    {
      "page": "tab_metrics",
      "title": "Output a table with distribution parameters",
      "topics": [
        "tab_metrics"
      ]
    },
    {
      "page": "theme_vlkr",
      "title": "Define a default theme for volker plots",
      "topics": [
        "theme_vlkr"
      ]
    }
  ],
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    "svglite",
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      "title": "Introduction",
      "engine": "knitr::rmarkdown",
      "headings": [
        "How to use the volkeR package?",
        "How to generate tables and plots?",
        "Categorical variables",
        "Metric variables",
        "Cross tabulation and group comparison",
        "Theming",
        "Labeling",
        "The volker report template",
        "Custom tab sheets",
        "Index calculation for item batteries",
        "Factor and cluster analysis",
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        "Reliability Scores and Classification Performance Indicators",
        "The mystery of missing values",
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      "created": "2023-09-30 07:06:32",
      "modified": "2026-01-10 14:37:21",
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