期刊名称：SORT-Statistics and Operations Research Transactions
印刷版ISSN：2013-8830
出版年度：2019
卷号：1
期号：1
页码：51-74
DOI：10.2436/20.8080.02.79
出版社：SORT- Statistics and Operations Research Transactions
摘要：In this paper we propose a Bayesian hierarchical spatio-temporal model for the joint analysis of multiple diseases which includes specific and shared spatial and temporal effects. Dependence on shared terms is controlled by disease-specific weights so that their posterior distribution can be used to identify diseases with similar spatial and temporal patterns. The model proposed here has been used to study three different causes of death (oral cavity, esophagus and stomach cancer) in Spain at the province level. Shared and specific spatial and temporal effects have been estimated and mapped in order to study similarities and differences among these causes. Furthermore, estimates using Markov chain Monte Carlo and the integrated nested Laplace approximation are compared.
