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|Title: ||A generalized ordered logit analysis of risk factors associated with driver injury severity|
|Authors: ||Aidoo, Eric Nimako|
|Keywords: ||Driver injury severity|
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|
|Appears in Collections:||College of Science|
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