{
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  "Package": "APCtools",
  "Title": "Routines for Descriptive and Model-Based APC Analysis",
  "Version": "1.0.8",
  "Authors@R": "c(\nperson(given = \"Alexander\",  family = \"Bauer\",   email = \"baueralexander@posteo.de\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-3495-5131\")),\nperson(given = \"Maximilian\", family = \"Weigert\", role = \"aut\", comment = c(ORCID = \"0000-0003-4400-134X\")),\nperson(given = \"Hawre\",      family = \"Jalal\",   email = \"hjalal@uottawa.ca\", role = \"aut\", comment=c(ORCID = \"0000-0002-8224-6834\")))",
  "Maintainer": "Alexander Bauer <baueralexander@posteo.de>",
  "Description": "Age-Period-Cohort (APC) analyses are used to differentiate\nrelevant drivers for long-term developments. The 'APCtools'\npackage offers visualization techniques and general routines to\nsimplify the workflow of an APC analysis. Sophisticated\nfunctions are available both for descriptive and regression\nmodel-based analyses. For the former, we use density (or\nridgeline) matrices and (hexagonally binned) heatmaps as\ninnovative visualization techniques building on the concept of\nLexis diagrams. Model-based analyses build on the separation of\nthe temporal dimensions based on generalized additive models,\nwhere a tensor product interaction surface (usually between age\nand period) is utilized to represent the third dimension\n(usually cohort) on its diagonal. Such tensor product surfaces\ncan also be estimated while accounting for further covariates\nin the regression model. See Weigert et al. (2021)\n<doi:10.1177/1354816620987198> for methodological details.",
  "License": "MIT + file LICENSE",
  "URL": "https://bauer-alex.github.io/APCtools/",
  "BugReports": "https://github.com/bauer-alex/APCtools/issues",
  "Encoding": "UTF-8",
  "LazyData": "true",
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  "VignetteBuilder": "knitr",
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  "Config/pak/sysreqs": "cmake make libicu-dev",
  "Repository": "https://bauer-alex.r-universe.dev",
  "Date/Publication": "2025-06-18 19:07:27 UTC",
  "RemoteUrl": "https://github.com/bauer-alex/apctools",
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    "User": "root"
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  "Author": "Alexander Bauer [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-3495-5131>),\nMaximilian Weigert [aut] (ORCID:\n<https://orcid.org/0000-0003-4400-134X>),\nHawre Jalal [aut] (ORCID: <https://orcid.org/0000-0002-8224-6834>)",
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  "_user": "bauer-alex",
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    "extra/citation.cff",
    "extra/citation.html",
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    "create_modelSummary",
    "plot_1Dsmooth",
    "plot_APCheatmap",
    "plot_APChexamap",
    "plot_density",
    "plot_densityMatrix",
    "plot_jointMarginalAPCeffects",
    "plot_linearEffects",
    "plot_marginalAPCeffects",
    "plot_partialAPCeffects",
    "plot_variable"
  ],
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      "name": "drug_deaths",
      "title": "Drug deaths of white men in the United States",
      "object": "drug_deaths",
      "class": [
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      ],
      "fields": [
        "period",
        "age",
        "deaths",
        "population",
        "mortality_rate"
      ],
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      "table": true,
      "tojson": true
    },
    {
      "name": "travel",
      "title": "Data from the German Reiseanalyse survey",
      "object": "travel",
      "class": [
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        "tbl",
        "data.frame"
      ],
      "fields": [
        "period",
        "age",
        "sampling_weight",
        "german_citizenship",
        "residence_region",
        "household_size",
        "household_income",
        "mainTrip_duration",
        "mainTrip_distance"
      ],
      "rows": 32717,
      "table": true,
      "tojson": true
    }
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  "_help": [
    {
      "page": "calc_density",
      "title": "Internal helper to calculate the (group-specific) density of a variable",
      "topics": [
        "calc_density"
      ]
    },
    {
      "page": "capitalize_firstLetter",
      "title": "Internal function to capitalize the first letter of a character",
      "topics": [
        "capitalize_firstLetter"
      ]
    },
    {
      "page": "compute_marginalAPCeffects",
      "title": "Internal helper to compute marginal APC effects and their confidence intervals",
      "topics": [
        "compute_marginalAPCeffects"
      ]
    },
    {
      "page": "compute_xCoordinate",
      "title": "Internal helper to tilt the x-axis for the hexamap plot",
      "topics": [
        "compute_xCoordinate"
      ]
    },
    {
      "page": "compute_yCoordinate",
      "title": "Internal helper to tilt the x-axis for the hexamap plot",
      "topics": [
        "compute_yCoordinate"
      ]
    },
    {
      "page": "create_APCsummary",
      "title": "Create a summary table for multiple estimated GAM models",
      "topics": [
        "create_APCsummary"
      ]
    },
    {
      "page": "create_groupVariable",
      "title": "Internal helper to create a group variable as base for a density matrix",
      "topics": [
        "create_groupVariable"
      ]
    },
    {
      "page": "create_highlightDiagonalData",
      "title": "Internal helper to create a dataset for ggplot2 to highlight diagonals",
      "topics": [
        "create_highlightDiagonalData"
      ]
    },
    {
      "page": "create_modelSummary",
      "title": "Create model summary tables for multiple estimated GAM models",
      "topics": [
        "create_modelSummary"
      ]
    },
    {
      "page": "create_oneAPCsummaryTable",
      "title": "Internal helper to create a summary table for one estimated GAM model",
      "topics": [
        "create_oneAPCsummaryTable"
      ]
    },
    {
      "page": "drug_deaths",
      "title": "Drug deaths of white men in the United States",
      "topics": [
        "drug_deaths"
      ]
    },
    {
      "page": "ensure_segmentsInPlotRange",
      "title": "Internal helper for gg_addReferenceLines to keep diagonal lines in the plot range",
      "topics": [
        "ensure_segmentsInPlotRange"
      ]
    },
    {
      "page": "extract_summary_linearEffects",
      "title": "Internal helper to extract summary of linear effects in a gam model",
      "topics": [
        "extract_summary_linearEffects"
      ]
    },
    {
      "page": "get_plotGAMobject",
      "title": "Extract returned values of plot.gam() while suppressing creation of the plot",
      "topics": [
        "get_plotGAMobject"
      ]
    },
    {
      "page": "gg_addReferenceLines",
      "title": "Internal helper to add reference lines in an APC heatmap",
      "topics": [
        "gg_addReferenceLines"
      ]
    },
    {
      "page": "gg_highlightDiagonals",
      "title": "Internal helper to add the diagonal highlighting to a ggplot",
      "topics": [
        "gg_highlightDiagonals"
      ]
    },
    {
      "page": "plot_1Dsmooth",
      "title": "Plot 1D smooth effects for 'gam' models",
      "topics": [
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      ]
    },
    {
      "page": "plot_APCheatmap",
      "title": "Heatmap of an APC surface",
      "topics": [
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      ]
    },
    {
      "page": "plot_APChexamap",
      "title": "Hexamap of an APC surface",
      "topics": [
        "plot_APChexamap"
      ]
    },
    {
      "page": "plot_density",
      "title": "Plot the density of one metric or categorical variable",
      "topics": [
        "plot_density"
      ]
    },
    {
      "page": "plot_density_categorical",
      "title": "Internal helper to plot a categorical density",
      "topics": [
        "plot_density_categorical"
      ]
    },
    {
      "page": "plot_density_metric",
      "title": "Internal helper to plot a metric density",
      "topics": [
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      ]
    },
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      "title": "Create a matrix of density plots",
      "topics": [
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      ]
    },
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      "title": "Plot of marginal APC effects based on an estimated GAM model",
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    },
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      "title": "Distribution plot of one variable against one APC dimension",
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      ]
    },
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      "title": "Data from the German Reiseanalyse survey",
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      "title": "APC Analysis with APCtools",
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      "engine": "knitr::rmarkdown",
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        "Load relevant packages",
        "Example data",
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