Adjusting statistical benchmark risk analysis to account for non-spatial autocorrelation, with application to natural hazard risk assessment
AffiliationInterdisciplinary Program in Statistics & Data Science, University of Arizona
BIO5 Institute, University of Arizona
Department of Mathematics, University of Arizona
centered autologistic model
natural hazard vulnerability
quantitative risk assessment
MetadataShow full item record
PublisherTaylor and Francis Ltd.
CitationLiu, J., Piegorsch, W. W., Schissler, A. G., McCaster, R. R., & Cutter, S. L. (2021). Adjusting statistical benchmark risk analysis to account for non-spatial autocorrelation, with application to natural hazard risk assessment. Journal of Applied Statistics, 1-21.
JournalJournal of Applied Statistics
Rights© 2021 Informa UK Limited, trading as Taylor & Francis Group
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractWe 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. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
Note12 month embargo; first published online 1 April 2021
VersionFinal accepted manuscript
SponsorsNational Institute of Environmental Health Sciences