Age-Period-Cohort (APC) analyses are used to differentiate relevant drivers for long-term developments. The 'APCtools' package offers visualization techniques and general routines to simplify the workflow of an APC analysis. Sophisticated functions are available both for descriptive and regression model-based analyses. For the former, we use density (or ridgeline) matrices and (hexagonally binned) heatmaps as innovative visualization techniques building on the concept of Lexis diagrams. Model-based analyses build on the separation of the temporal dimensions based on generalized additive models, where a tensor product interaction surface (usually between age and period) is utilized to represent the third dimension (usually cohort) on its diagonal. Such tensor product surfaces can also be estimated while accounting for further covariates in the regression model. See Weigert et al. (2021) <doi:10.1177/1354816620987198> for methodological details.
Version: 1.0.8 Depends: R (≥ 3.5) Imports: ggpubr, checkmate, knitr, ggplot2, colorspace, dplyr, mgcv, scales, tidyr, stringr Suggests: testthat (≥ 3.0.0), rmarkdown, covr Published: 2025-06-18 DOI: 10.32614/CRAN.package.APCtools Author: Alexander Bauer [aut, cre], Maximilian Weigert [aut], Hawre Jalal [aut] Maintainer: Alexander Bauer <baueralexander at posteo.de> BugReports: https://github.com/bauer-alex/APCtools/issues License: MIT + file LICENSE URL: https://bauer-alex.github.io/APCtools/ NeedsCompilation: no Materials: README NEWS CRAN checks: APCtools results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=APCtools to link to this page.
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