A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities

Fountas, Grigorios; Anastasopoulos, Panagiotis Ch.

Abstract

This study uses highway accident data collected in the State of Washington, between 2011 and 2013, to study the factors that affect accident injury-severities. To account for the fixed thresholds limitation of the traditional ordered probability models – which typically leads to incorrect estimation of outcome probabilities for the intermediate categories – and for the possibility of unobserved factors systematically varying across the observations, a random thresholds hierarchical ordered probit model with random parameters is estimated. This approach simultaneously allows the explanatory parameters to vary across roadway segments, and the thresholds to vary both as a function of explanatory parameters and across the observations, thus accounting for unobserved and threshold heterogeneity, respectively. Using goodness-of-fit measures, likelihood ratio tests and forecasting accuracy measures, the model estimation results are compared with the hierarchical and fixed thresholds ordered probit model counterparts, with fixed and random parameters. The comparative assessment among the ordered probit modeling approaches reveals the relative benefits and the overall statistical superiority of the random thresholds random parameters hierarchical ordered probit model.

Citation

Fountas, G., & Anastasopoulos, P. C. (2017). A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities. Analytic Methods in Accident Research, 15, 1-16. https://doi.org/10.1016/j.amar.2017.03.002

• Journal Article Type: Article
• Acceptance Date: Mar 25, 2017
• Online Publication Date: Apr 26, 2017
• Publication Date: 2017-09
• Deposit Date: Sep 20, 2018
• Journal: Analytic Methods in Accident Research
• Print ISSN: 2213-6657
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 15
• Pages: 1-16
• DOI: https://doi.org/10.1016/j.amar.2017.03.002
• Keywords: Accident injury-severities, Hierarchical ordered probit, Random thresholds, Random parameters
• Public URL: http://researchrepository.napier.ac.uk/Output/1302882