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A common goal in modeling demographic rates is to compare two or more groups.For ex- ample comparing mortality rates between men and women or betweengeographic regions may reveal health inequalities. A popular class of modelsfor all-cause mortality as well as incidence of specific diseases like canceris the age-period-cohort (APC) model. Extending this model to the multivariatesetting is not straightforward because the univariate APC model suffers fromwell-known identifiability problems. Often APC models are fit separately foreach strata, and then comparisons are made post hoc. This paper introduces astratified APC model to directly assess the sources of heterogeneity inmortality rates using a Bayesian hierarchical model with matrix-normal priorsthat share information on linear and nonlinear aspects of the APC effectsacross strata. Computing, model selection, and prior specification areaddressed and the model is then applied to all-cause mortality data from theEuropean Union.

A stratified age-period-cohort model for spatial heterogeneity in all-cause mortality