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Autologistic models for benchmark risk or vulnerability assessment of urban terrorism outcomes.
- Source :
-
Journal of the Royal Statistical Society. Series A, (Statistics in Society) [J R Stat Soc Ser A Stat Soc] 2018 Jun; Vol. 181 (3), pp. 803-823. Date of Electronic Publication: 2017 Oct 10. - Publication Year :
- 2018
-
Abstract
- We develop a quantitative methodology to characterize vulnerability among 132 U.S. urban centers ('cities') to terrorist events, applying a place-based vulnerability index to a database of terrorist incidents and related human casualties. A centered autologistic regression model is employed to relate urban vulnerability to terrorist outcomes and also to adjust for autocorrelation in the geospatial data. Risk-analytic 'benchmark' techniques are then incorporated into the modeling framework, wherein levels of high and low urban vulnerability to terrorism are identified. This new, translational adaptation of the risk-benchmark approach, including its ability to account for geospatial autocorrelation, is seen to operate quite flexibly in this socio-geographic setting.
Details
- Language :
- English
- ISSN :
- 0964-1998
- Volume :
- 181
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Journal of the Royal Statistical Society. Series A, (Statistics in Society)
- Publication Type :
- Academic Journal
- Accession number :
- 29904240
- Full Text :
- https://doi.org/10.1111/rssa.12323