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dc.contributor.authorMOONS, Elke-
dc.contributor.authorFAES, Christel-
dc.contributor.authorBRIJS, Tom-
dc.identifier.citationJoint Statistical Meetings 2009.-
dc.description.abstractTraffic accidents are still a major cause of death all over the world. Within the age groups up to 44 years, it even holds an unfortunate third place. Hence, it is not surprisingly that traffic safety has become a 'hot' topic for policy makers, in the media, for academics as well as for a broad audience. However, in order to make the step from evidence to policy, risk models play an important role. This paper focuses on fitting increasingly complex models for the estimation of the relative accident risk in small areas, here applied to communities in Belgium. The most classical model is the Poisson model that will be extended to hierarchical models, such as the Poisson-Gamma or the Poisson-lognormal model, and even the spatial correlation structure will be taken into account via different ways. The results are compared to each other based on several goodness-of-fit measures.-
dc.subject.otherspatial statistics; risk model; Bayesian mapping; Poisson regression; traffic safety-
dc.subject.otherspatial statistics ; risk model ; Bayesian mapping ; Poisson regression ; traffic safety-
dc.titleRisk assessment in traffic safety-
dc.typeProceedings Paper-
local.bibliographicCitation.conferencenameJoint Statistical Meetings 2009-
local.bibliographicCitation.conferenceplaceWashington, D.C.-
local.bibliographicCitation.btitleJoint Statistical Meetings 2009-
item.fulltextNo Fulltext-
item.contributorBRIJS, Tom-
item.contributorFAES, Christel-
item.contributorMOONS, Elke-
item.fullcitationMOONS, Elke; FAES, Christel & BRIJS, Tom (2009) Risk assessment in traffic safety. In: Joint Statistical Meetings 2009..-
item.accessRightsClosed Access-
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