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: | 2.0.0 |
| Imports: | lattice, plyr, reshape, plm, survey, lmtest, car, ISLR, AER, ggplot2, ChainLadder |
| Published: | 2020-10-01 |
| Author: | Zoe Fannon, Bent Nielsen |
| Maintainer: | Bent Nielsen <bent.nielsen at nuffield.ox.ac.uk> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | apc results |
| Reference manual: | apc.pdf |
| Vignettes: |
Identification: illustrate and check identification used in plot fit function Introduction: analysis of aggregate data Introduction: analysis of individual data Introduction: analysis of individual data: further examples Generating new models from design matrix function Reproducing HN2016 Reproducing KN2020 Illustrate and check identification used in plot fit function Reproducing MMNN2016 |
| Package source: | apc_2.0.0.tar.gz |
| Windows binaries: | r-devel: apc_2.0.0.zip, r-release: apc_2.0.0.zip, r-oldrel: apc_2.0.0.zip |
| macOS binaries: | r-release: apc_2.0.0.tgz, r-oldrel: apc_2.0.0.tgz |
| Old sources: | apc archive |
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