Abstract
Age-period-cohort models have a long and interesting history and area popular choice in a number of disciplines, includingepidemiology, demography, and the social sciences. However, the fitting and interpretation ofthese models requires great care because of the well-knownidentifiability problem that exists; given any two of age, period, andcohort, the third is determined.In this paper we review the identifiability problem and models thathave been proposed for analysis, from both frequentist and Bayesian standpoints. Anumber of recent analyses that use age-period-cohort models aredescribed and critiqued before data on cancer incidence in WashingtonState are analyzed with various models, including a new hybridBayesian approach based on an identifiable parameterization.
Original language | English |
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Pages (from-to) | 591-610 |
Journal | Statistical Science |
Volume | 31 |
Issue number | 4 |
DOIs | |
Publication status | Published - 19 Jan 2017 |
Keywords
- age-period-cohort models
- identifiability
- random walk priors
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Theresa Smith
- Department of Mathematical Sciences - Senior Lecturer
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
- Centre for Mathematics and Algorithms for Data (MAD)
- Centre for Therapeutic Innovation
- Bath Institute for the Augmented Human
- Centre of Excellence in Water-Based Early-Warning Systems for Health Protection (CWBE)
Person: Research & Teaching, Core staff, Affiliate staff