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: not available, 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_2.0.0.tgz, r-oldrel (x86_64): apc_2.0.0.tgz
Old sources: apc archive

Reverse dependencies:

Reverse suggests: clmplus

Linking:

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