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apc: Age-Period-Cohort Analysis

Functions for age-period-cohort analysis. Aggregate data can be organised in matrices indexed by age-cohort, age-period or cohort-period. The data can include dose and response or just doses. The statistical model is a generalized linear model (GLM) allowing for 3,2,1 or 0 of the age-period-cohort factors. Individual-level data should have a row for each individual and columns for each of age, period, and cohort. The statistical model for repeated cross-section is a generalized linear model. The statistical model for panel data is ordinary least squares. The canonical parametrisation of Kuang, Nielsen and Nielsen (2008) <doi:10.1093/biomet/asn026> is used. Thus, the analysis does not rely on ad hoc identification.

Version: 2.0.1
Imports: lattice, plyr, reshape, plm, survey, lmtest, car, AER, ISLR, ggplot2
Published: 2025-06-15
DOI: 10.32614/CRAN.package.apc
Author: Zoe Fannon [aut], Bent Nielsen [aut, cre]
Maintainer: Bent Nielsen <bent.nielsen at nuffield.ox.ac.uk>
License: GPL-3
NeedsCompilation: no
In views: ActuarialScience
CRAN checks: apc results

Documentation:

Reference manual: apc.pdf
Vignettes: Identification: illustrate and check identification used in plot fit function (source, R code)
Introduction: analysis of aggregate data (source, R code)
Introduction: analysis of individual data (source, R code)
Introduction: analysis of individual data: further examples (source, R code)
Generating new models from design matrix function (source, R code)
Reproducing HN2016 (source, R code)
Reproducing KN2020 (source, R code)
Illustrate and check identification used in plot fit function (source, R code)
Reproducing MMNN2016 (source, R code)

Downloads:

Package source: apc_2.0.1.tar.gz
Windows binaries: r-devel: apc_2.0.1.zip, r-release: apc_2.0.1.zip, r-oldrel: apc_2.0.1.zip
macOS binaries: r-release (arm64): apc_2.0.1.tgz, r-oldrel (arm64): apc_2.0.1.tgz, r-release (x86_64): apc_2.0.1.tgz, r-oldrel (x86_64): apc_2.0.1.tgz
Old sources: apc archive

Reverse dependencies:

Reverse suggests: clmplus

Linking:

Please use the canonical form https://CRAN.R-project.org/package=apc to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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