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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/14452

Title: A generalized ordered logit analysis of risk factors associated with driver injury severity
Authors: Aidoo, Eric Nimako
Ackaah, Williams
Keywords: Driver injury severity
Ordered response
Generalized ordered logit model
Issue Date: 2019
Publisher: Journal of Public Health: From Theory to Practice
Citation: Journal of Public Health: From Theory to Practice, 2019; https://doi.org/10.1007/s10389-019-01135-8
Abstract: Aim Road traffic crashes remain a major public health issue and have been the subject of debate in many studies due to their effect on society. This study contributes to the discussion by investigating the risk factors that significantly contribute to driver injury severity sustained in traffic crashes. Subject and methods Using the crash data from the Greater Accra region of Ghana, spanning a 3-year period (2014– 2016), a generalized ordered logit (GOL) model was estimated to determine the effect of a wide range of variables on driver injury severity outcome. Results The results suggest that, in the event of a crash, more severe driver injury was influenced by multiple factors including driver’s gender, driver’s action (e.g., turning, overtaking, going ahead), number of vehicles involved, day of week of the crash, vehicle size, and road width. Conclusion The findings of this study highlight the need to further study risk factors significantly influencing driver injury severity.
Description: An article published in Journal of Public Health: From Theory to Practice, 2019; https://doi.org/10.1007/s10389-019-01135-8
URI: http://hdl.handle.net/123456789/14452
Appears in Collections:College of Science

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