Citation

Al-Ghamdi AS. Accid. Anal. Prev. 2002; 34(6): 729-741.

Affiliation

College of Engineering, King Saud University, Riyadh, Saudi Arabia. asghamdi@ksu.edu.sa

Copyright

(Copyright © 2002, Elsevier Publishing)

DOI

unavailable

PMID

12371778

Abstract

Logistic regression was applied to accident-related data collected from traffic police records in order to examine the contribution of several variables to accident severity. A total of 560 subjects involved in serious accidents were sampled. Accident severity (the dependent variable) in this study is a dichotomous variable with two categories, fatal and non-fatal. Therefore, each of the subjects sampled was classified as being in either a fatal or non-fatal accident. Because of the binary nature of this dependent variable, a logistic regression approach was found suitable. Of nine independent variables obtained from police accident reports, two were found most significantly associated with accident severity, namely, location and cause of accident. A statistical interpretation is given of the model-developed estimates in terms of the odds ratio concept. The findings show that logistic regression as used in this research is a promising tool in providing meaningful interpretations that can be used for future safety improvements in Riyadh.