apc.identify.mixed

Generalizes <code>apc.identify</code> to mixed frequency data.

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. 2-sample analysis is possible. Mixed frequency data are possible. 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.

Bent Nielsen

Age-Period-Cohort Analysis

Zoe Fannon

apc.identify.mixed function

<dl> <dt>apc.fit.model</dt>
<dd>List. See <code>apc.fit.model</code> for a description of the format.</dd></dl>

Arguments

Bent Nielsen &lt;bent.nielsen@nuffield.ox.ac.uk&gt; 3 Jul 2025

Author

Identification of time effects for mixed frequency data — apc.identify.mixed

<dl>

 <dt>apc.fit.model</dt>
<dd>List. See <code>apc.fit.model</code> for a description of the format.</dd>

</dl>

apc.identify.mixed: Identification of time effects for mixed frequency data

Description

Usage

Arguments

Author

References