Adjusting statistical benchmark risk analysis to account for non-spatial autocorrelation, with application to natural hazard risk assessment.
Benchmark dose
centered autologistic model
maximum pseudo-likelihood
natural hazard vulnerability
non-spatial autocorrelation
quantitative risk assessment
Journal
Journal of applied statistics
ISSN: 0266-4763
Titre abrégé: J Appl Stat
Pays: England
ID NLM: 9883455
Informations de publication
Date de publication:
2022
2022
Historique:
entrez:
27
6
2022
pubmed:
1
4
2021
medline:
1
4
2021
Statut:
epublish
Résumé
We develop and study a quantitative, interdisciplinary strategy for conducting statistical risk analyses within the 'benchmark risk' paradigm of contemporary risk assessment when potential autocorrelation exists among sample units. We use the methodology to explore information on vulnerability to natural hazards across 3108 counties in the conterminous 48 US states, applying a place-based resilience index to an existing knowledgebase of hazardous incidents and related human casualties. An extension of a centered autologistic regression model is applied to relate local, county-level vulnerability to hazardous outcomes. Adjustments for autocorrelation embedded in the resiliency information are applied via a novel, non-spatial neighborhood structure. Statistical risk-benchmarking techniques are then incorporated into the modeling framework, wherein levels of high and low vulnerability to hazards are identified.
Identifiants
pubmed: 35755089
doi: 10.1080/02664763.2021.1904385
pii: 1904385
pmc: PMC9225316
doi:
Types de publication
Journal Article
Langues
eng
Pagination
2349-2369Informations de copyright
© 2021 Informa UK Limited, trading as Taylor & Francis Group.
Déclaration de conflit d'intérêts
No potential conflict of interest was reported by the author(s).
Références
Ambio. 2002 Aug;31(5):437-40
pubmed: 12374053
Fundam Appl Toxicol. 1984 Oct;4(5):854-71
pubmed: 6510615
J R Stat Soc Ser A Stat Soc. 2018 Jun;181(3):803-823
pubmed: 29904240
Biometrics. 2001 Sep;57(3):698-706
pubmed: 11550917
Biometrics. 2005 Mar;61(1):277-86
pubmed: 15737104
Disasters. 2006 Dec;30(4):433-50
pubmed: 17100752
Proc Natl Acad Sci U S A. 2017 Sep 19;114(38):10077-10082
pubmed: 28874573
Environmetrics. 2013 May 1;24(3):143-157
pubmed: 24039461