Journal
ACCIDENT ANALYSIS AND PREVENTION
Volume 39, Issue 6, Pages 1267-1278Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.aap.2007.03.017
Keywords
binary logistic regression; pedestrian casualty; injury severity; interaction effect; Hosmer-Lemeshow statistic; logistic regression diagnostics
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This study attempts to evaluate the injury risk of pedestrian casualties in traffic crashes and to explore the factors that contribute to mortality and severe injury, using the comprehensive historical crash record that is maintained by the Hong Kong Transport Department. The injury, demographic, crash, environmental, geometric, and traffic characteristics of 73,746 pedestrian casualties that were involved in traffic crashes from 1991 to 2004 are considered. Binary logistic regression is used to determine the associations between the probability of fatality and severe injury and all contributory factors. A consideration of the influence of implicit attributes on the trend of pedestrian injury risk, temporal confounding, and interaction effects is progressively incorporated into the predictive model. To verify the goodness-of-fit of the proposed model, the Hosmer-Lemeshow test and logistic regression diagnostics are conducted. It is revealed that there is a decreasing trend in pedestrian injury risk, controlling for the influences of demographic, road environment, and other risk factors. In addition, the influences of pedestrian behavior, traffic congestion, and junction type on pedestrian injury risk are subject to temporal variation. (C) 2007 Elsevier Ltd. All rights reserved.
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