On the use of adaptive spatial weight matrices from disease mapping multivariate analyses
NAGIOS: RODERIC FUNCIONANDO

On the use of adaptive spatial weight matrices from disease mapping multivariate analyses

DSpace Repository

On the use of adaptive spatial weight matrices from disease mapping multivariate analyses

Show simple item record

dc.contributor.author Corpas Burgos, Francisca
dc.contributor.author Martínez Beneito, Miguel Ángel
dc.date.accessioned 2021-02-08T16:51:40Z
dc.date.available 2021-02-08T16:51:40Z
dc.date.issued 2020
dc.identifier.uri https://hdl.handle.net/10550/77713
dc.description.abstract Conditional autoregressive distributions are commonly used to model spatial dependence between nearby geographic units in disease mapping studies. These distributions induce spatial dependence by means of a spatial weights matrix that quantifies the strength of dependence between any two neighboring spatial units. The most common procedure for defining that spatial weights matrix is using an adjacency criterion. In that case, all pairs of spatial units with adjacent borders are given the same weight (typically 1) and the remaining non-adjacent units are assigned a weight of 0. However, assuming all spatial neighbors in a model to be equally influential could be possibly a too rigid or inappropriate assumption. In this paper, we propose several adaptive conditional autoregressive distributions in which the spatial weights for adjacent areas are random variables, and we discuss their use in spatial disease mapping models. We will introduce our proposal in a multivariate context so that the spatial dependence structure between spatial units is shared and estimated from a sufficiently large set of mortality causes. As we will see, this is a key aspect for making inference on the spatial dependence structure. We show that our adaptive modeling proposal provides more flexible and accurate mortality risk estimates than traditional proposals in which spatial weights for neighboring areas are fixed to a common value.
dc.language.iso eng
dc.relation.ispartof Stochastic Environmental Research and Risk Assessment, 2020, vol. 34, p. 531-544
dc.rights.uri info:eu-repo/semantics/openAccess
dc.source Corpas Burgos, Francisca Martínez Beneito, Miguel Ángel 2020 On the use of adaptive spatial weight matrices from disease mapping multivariate analyses Stochastic Environmental Research and Risk Assessment 34 531 544
dc.subject Estadística
dc.subject Processos estocàstics
dc.subject Malalties
dc.title On the use of adaptive spatial weight matrices from disease mapping multivariate analyses
dc.type info:eu-repo/semantics/article
dc.date.updated 2021-02-08T16:51:41Z
dc.identifier.doi https://doi.org/10.1007/s00477-020-01781-5
dc.identifier.idgrec 143219

View       (997.0Kb)

This item appears in the following Collection(s)

Show simple item record

Search DSpace

Advanced Search

Browse

Statistics