Publication: High-dimensional order-free multivariate spatial disease mapping
| dc.contributor.author | Vicente Fuenzalida, Gonzalo | |
| dc.contributor.author | Adin Urtasun, Aritz | |
| dc.contributor.author | Goicoa Mangado, Tomás | |
| dc.contributor.author | Ugarte Martínez, María Dolores | |
| dc.contributor.department | Estadística, Informática y Matemáticas | es_ES |
| dc.contributor.department | Estatistika, Informatika eta Matematika | eu |
| dc.contributor.department | Institute for Advanced Materials and Mathematics - INAMAT2 | en |
| dc.contributor.funder | Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA2001 | es |
| dc.date.accessioned | 2023-09-14T07:52:26Z | |
| dc.date.available | 2023-09-14T07:52:26Z | |
| dc.date.issued | 2023 | |
| dc.date.updated | 2023-09-14T07:41:27Z | |
| dc.description.abstract | Despite the amount of research on disease mapping in recent years, the use of multivariate models for areal spatial data remains limited due to difficulties in implementation and computational burden. These problems are exacerbated when the number of areas is very large. In this paper, we introduce an order-free multivariate scalable Bayesian modelling approach to smooth mortality (or incidence) risks of several diseases simultaneously. The proposal partitions the spatial domain into smaller subregions, fits multivariate models in each subdivision and obtains the posterior distribution of the relative risks across the entire spatial domain. The approach also provides posterior correlations among the spatial patterns of the diseases in each partition that are combined through a consensus Monte Carlo algorithm to obtain correlations for the whole study region. We implement the proposal using integrated nested Laplace approximations (INLA) in the R package bigDM and use it to jointly analyse colorectal, lung, and stomach cancer mortality data in Spanish municipalities. The new proposal allows for the analysis of large datasets and yields superior results compared to fitting a single multivariate model. Additionally, it facilitates statistical inference through local homogeneous models, which may be more appropriate than a global homogeneous model when dealing with a large number of areas. | en |
| dc.description.sponsorship | This work has been supported by the project PID2020-113125RB-I00/MCIN/AEI/10.13039/501100011033. It has also been partially funded by the Public University of Navarra (project PJUPNA2001). Open Access funding provided by Universidad Pública de Navarra. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Vicente, G., Adin, A., Goicoa, T., & Ugarte, M. D. (2023). High-dimensional order-free multivariate spatial disease mapping. Statistics and Computing, 33(5), 104. https://doi.org/10.1007/s11222-023-10263-x | en |
| dc.identifier.doi | 10.1007/s11222-023-10263-x | |
| dc.identifier.issn | 0960-3174 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/46321 | |
| dc.language.iso | eng | en |
| dc.publisher | Springer | en |
| dc.relation.ispartof | Statistics and Computing, (2023) 33:104 | en |
| dc.relation.projectID | nfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113125RB-I00/ES/ | en |
| dc.relation.publisherversion | https://doi.org/10.1007/s11222-023-10263-x | |
| dc.rights | © The author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License | en |
| dc.rights.accessRights | Acceso abierto / Sarbide irekia | es |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Bayesian inference | en |
| dc.subject | High-dimensional data | en |
| dc.subject | Scalable models | en |
| dc.subject | Spatial epidemiology | en |
| dc.title | High-dimensional order-free multivariate spatial disease mapping | en |
| dc.type | Artículo / Artikulua | es |
| dc.type | info:eu-repo/semantics/article | en |
| dc.type.version | Versión publicada / Argitaratu den bertsioa | es |
| dc.type.version | info:eu-repo/semantics/publishedVersion | en |
| dspace.entity.type | Publication | |
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