APCtools

APCtools: Descriptive and Model-based Age-Period-Cohort Analysis - Published in JOSS (2022)

https://github.com/bauer-alex/apctools

Scientific Fields

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Descriptive and model-based tools for Age-Period-Cohort analyses

README.Rmd

---
output: github_document
---

```{r options, echo=FALSE}
library(knitr)
opts_chunk$set(warning=FALSE)
```

# APCtools 


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Routines for Descriptive and Model-Based APC Analysis

* Authors: [Alexander Bauer](https://github.com/bauer-alex), Maximilian Weigert, [Hawre Jalal](https://www.uottawa.ca/faculty-medicine/dr-hawre-jalal)
* Version: 1.0.8


## Aim of this Package

Age-Period-Cohort (APC) analysis aims to determine relevant drivers for
long-term developments and is used in many fields of science.
The main focus is on disentangling the interconnected effects of age, period, and
cohort.
Long-term developments of some characteristic can either be associated
with changes in a person's life cycle (age), macro-level developments over the years
that simultaneously affect all age groups (period), or the generational
membership of an individual, shaped by similar socialization processes and historical experiences
(cohort).
The critical challenge in APC analysis is the linear dependency of the
components age, period, and cohort (cohort = period - age).
Accordingly, flexible methods and visualization techniques are needed to properly
disentangle observed temporal association structures.

In contrast to other software packages, `APCtools` builds on a flexible and robust
semiparametric regression approach to circumvent this identification problem.
The package includes modern visualization techniques and general routines to facilitate
the interpretability of the estimated temporal structures and simplify the workflow
of an APC analysis.


## Main Functionality

Sophisticated functions are available both for descriptive and regression model-based analyses.
For the former, we use density (or ridgeline) matrices, classical heatmaps and
*hexamaps* (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.

## Documentation and Useful Materials

* To get an overview of the functionalities of the package, check out the
[JOSS publication](https://joss.theoj.org/papers/10.21105/joss.04056) or the
[package vignette](https://bauer-alex.github.io/APCtools/articles/main_functionality.html).

* See [Weigert et al. (2021)](https://doi.org/10.1177/1354816620987198) or
our corresponding [research poster](https://www.researchgate.net/publication/353852226_Visualization_techniques_for_semiparametric_APC_analysis_Using_Generalized_Additive_Models_to_examine_touristic_travel_distances)
for methodological details.
    
* Hexamaps as a concept for the visualization of APC structures are outlined in
[Jalal & Burke (2020)](https://doi.org/10.1097/EDE.0000000000001236).


## Installation

The most current version from GitHub can be installed via
```{r, eval=FALSE}
devtools::install_github("bauer-alex/APCtools")
```


## How to Contribute

If you encounter problems with the package, find bugs or have suggestions for
additional functionalities please open a
[GitHub issue](https://github.com/bauer-alex/APCtools/issues).
Alternatively, feel free to contact us directly via email.

Contributions (via pull requests or otherwise) are welcome.
Before you open a pull request or share your updates with us, please make sure
that all unit tests pass without errors or warning messages. You can run the unit
tests by calling
```r
devtools::test()
```

## References

Bauer, A., Weigert, M., and Jalal, H. (2022). APCtools: Descriptive and Model-based Age-Period-Cohort Analysis. Journal of Open Source Software, 7(73), 4056, https://doi.org/10.21105/joss.04056.

Weigert, M., Bauer, A., Gernert, J., Karl, M., Nalmpatian, A., Küchenhoff, H.,
and Schmude, J. (2021). Semiparametric APC analysis of destination choice
patterns: Using generalized additive models to quantify the impact of age,
period, and cohort on travel distances. *Tourism Economics*.
https://doi.org/10.1177/1354816620987198.

Jalal, H., Burke, D. (2020). Hexamaps for Age–Period–Cohort Data Visualization
and Implementation in R. *Epidemiology*, 31 (6), e47-e49. doi: https://doi.org/10.1097/EDE.0000000000001236.

Owner

JOSS Publication

APCtools: Descriptive and Model-based Age-Period-Cohort Analysis

Published

May 04, 2022

DOI

10.21105/joss.04056

Volume 7, Issue 73, Page 4056

Authors

Alexander Bauer
Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Germany

Maximilian Weigert
Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Germany

Hawre Jalal
Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh.

Editor

Nikoleta Glynatsi

Tags

Statistical analysis APC analysis Age period cohort analysis Hexamaps

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