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)