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Inference and forecasting in the age-period-cohort model with unknown exposure with an application to mesothelioma mortality

Martinez-Miranda, M. D., Nielsen, B. and Nielsen, J. P. (2014). Inference and forecasting in the age-period-cohort model with unknown exposure with an application to mesothelioma mortality. Journal of the Royal Statistical Society. Series A: Statistics in Society, 178(1), pp. 29-55. doi: 10.1111/rssa.12051

Abstract

It is of considerable interest to forecast future mesothelioma mortality. No measures for exposure are available so it is not straightforward to apply a dose–response model. It is proposed to model the counts of deaths directly by using a Poisson regression with an age–period–cohort structure, but without offset. Traditionally the age–period–cohort is viewed as suffering from an identification problem. It is shown how to reparameterize the model in terms of freely varying parameters, to avoid this problem. It is shown how to conduct inference and how to construct distribution forecasts.

Publication Type: Article
Additional Information: This is the accepted version of the following article: Martínez Miranda, M. D., Nielsen, B. and Nielsen, J. P. (2015), Inference and forecasting in the age–period–cohort model with unknown exposure with an application to mesothelioma mortality. Journal of the Royal Statistical Society: Series A (Statistics in Society), 178: 29–55, which has been published in final form at http://dx.doi.org/10.1111/rssa.12051
Publisher Keywords: Age–period–cohort, Forecasting, Identification, Mesothelioma, Mortality, Unknown exposure
Subjects: Q Science > QA Mathematics
Departments: Cass Business School > Actuarial Science & Insurance
URI: http://openaccess.city.ac.uk/id/eprint/4625
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