Age-period-cohort modeling
Mark J. Rutherford
Department of Health Sciences
University of Leicester, UK
[email protected]
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Paul C. Lambert
Department of Health Sciences
University of Leicester, UK
[email protected]
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John R. Thompson
Department of Health Sciences
University of Leicester, UK
[email protected]
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Abstract. Age–period–cohort models provide a useful method for modeling incidence
and mortality rates. It is well known that age–period–cohort models suffer
from an identifiability problem due to the exact relationship between the variables
(cohort = period − age). In 2007, Carstensen published an article advocating
the use of an analysis that models age, period, and cohort as continuous variables
through the use of spline functions (Carstensen, 2007, Statistics in Medicine 26:
3018–3045). Carstensen implemented his method for age–period–cohort models in
the Epi package for R. In this article, a new command is introduced, apcfit, that
performs the methods in Stata. The identifiability problem is overcome by forcing
constraints on either the period or cohort effects. The use of the command is illustrated
through an example relating to the incidence of colon cancer in Finland.
The example shows how to include covariates in the analysis.
View all articles by these authors:
Mark J. Rutherford, Paul C. Lambert, John R. Thompson
View all articles with these keywords:
apcfit, poprisktime, age–period–cohort models, incidence rates, mortality rates, Lexis diagrams
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