Disease mapping studies have been widely performed at univariate level, that is considering only one disease in the estimated models. Nonetheless, simultaneous modelling of different diseases can be a valuable tool both from the epidemiological and from the statistical point of view. In this paper we propose a model for multivariate disease mapping that generalizes the univariate conditional auto-regressive distribution. The proposed model is proven to be an effective alternative to existing multivariate models, mainly because it overcome some restrictive hypotheses underlying models previously proposed in this context. Model performances are checked via a simulation study and via application to a case study.

F. Greco, C. Trivisano (2009). A multivariate CAR model for improving the estimation of relative risks. STATISTICS IN MEDICINE, 28, 1707-1724 [10.1002/sim.3577].

A multivariate CAR model for improving the estimation of relative risks

GRECO, FEDELE PASQUALE;TRIVISANO, CARLO
2009

Abstract

Disease mapping studies have been widely performed at univariate level, that is considering only one disease in the estimated models. Nonetheless, simultaneous modelling of different diseases can be a valuable tool both from the epidemiological and from the statistical point of view. In this paper we propose a model for multivariate disease mapping that generalizes the univariate conditional auto-regressive distribution. The proposed model is proven to be an effective alternative to existing multivariate models, mainly because it overcome some restrictive hypotheses underlying models previously proposed in this context. Model performances are checked via a simulation study and via application to a case study.
2009
F. Greco, C. Trivisano (2009). A multivariate CAR model for improving the estimation of relative risks. STATISTICS IN MEDICINE, 28, 1707-1724 [10.1002/sim.3577].
F. Greco; C. Trivisano
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/77642
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