PARSIMONIOUS PARAMETERIZATION OF AGE-PERIOD-COHORT MODELS BY BAYESIAN SHRINKAGE - ERRATUM

Multivariate Age-Period-Cohort Models

Age-period-cohort (APC) models are used to analyse age-specific disease or mortality rates provided for several periods in time with respect to three time scales: age, period (calendar period during which the incidence or mortality rates were observed) and cohort (time of birth). Frequently, several sets of such age-specific rates are observed because data were recorded according to one further...

Deviance analysis of age-period-cohort models

Age-period-cohort models for Lexis diagrams are considered. The identification problem is addressed by reparametrizing the models in terms of freely varying parameters. The reparametrisation covers all three Lexis diagrams. A new plot of the unidentified time effects is suggested and interpreted. Deviance analysis covering a wide range of sub-models is presented. The methods are applied to Belg...

Description of cervical cancer mortality in Belgium using Bayesian age-period-cohort models

Different ICD (International Classification of Diseases) were used over time for death cause certification. In the Netherlands, the proportion of not-otherwise specified uterine cancer deaths was small over large periods and therefore internal reallocation could be used to estimate the corrected rates cervical cancer mortality. In Belgium, the proportion of improperly defined uterus deaths was ...

An analysis of Japanese liver cancer mortality data with Bayesian age–period–cohort models

Age–period–cohort (APC) models have been widely used in the analysis of incidence and mortality data. Bayesian APC models, in which multivariate Gaussian priors are incorporated on age, period and cohort effects, can evade the identifiability problem. Inference with integrated nested Laplace approximations (INLA) has recently been a useful tool. An application of the Bayesian APC models with IN...

Further information about the Bayesian age-period-cohort statistical model and its implementation in BAMP (Bayesian Age-period-cohort Modelling and Prediction) software