A note on accounting for underlying injury-severity states in statistical modeling of injury accident data

Fountas, Grigorios; Rye, Tom

Abstract

This study provides an empirical analysis of the severity outcomes of injury accidents (i.e., accidents that resulted in an injury-involved outcome) by exploring the possibility of two underlying injury-severity states: the minor-injury state and the ordered injury state. The former may reflect the generation mechanism of slight-injury accidents with limited potential to result in more severe injury outcomes, whereas, the latter may represent slight-injury accidents that share similarities with the mechanism of the more severe outcomes, in terms of their occurrence circumstances. To account for the possible presence of these two underlying regimes, a zero-inflated hierarchical ordered probit model with correlated disturbances is estimated using injury-severity data from single-vehicle accidents occurred in Scotland, UK between 2016 and 2017. The results of the empirical analysis provide statistical evidence on the possible presence of underlying states, with the identified effect of traditional driver-, vehicle-, roadway- and accident-specific determinants revealing the nuances and structural differences of such injury-severity states.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 10th International Conference on Ambient Systems, Networks and Technologies (ANT)
• Acceptance Date: Feb 2, 2019
• Online Publication Date: May 21, 2019
• Publication Date: May 21, 2019
• Deposit Date: Mar 18, 2019
• Publicly Available Date: Mar 18, 2019
• Journal: Procedia Computer Science
• Print ISSN: 1877-0509
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 151
• Pages: 202-209
• DOI: https://doi.org/10.1016/j.procs.2019.04.030
• Keywords: injury severity; single-vehicle accidents; underlying states; zero-inflated ordered probit; ordered thresholds
• Public URL: http://researchrepository.napier.ac.uk/Output/1668392
• Contract Date: Mar 18, 2019