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Article: Diagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes

TitleDiagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes
Authors
KeywordsBinary logistic regression
Hosmer-Lemeshow statistic
Injury severity
Interaction effect
Logistic regression diagnostics
Pedestrian casualty
Issue Date2007
PublisherElsevier Ltd. The Journal's web site is located at http://www.elsevier.com/wps/find/journaldescription.cws_home/336/description#description
Citation
Accident Analysis And Prevention, 2007, v. 39 n. 6, p. 1267-1278 How to Cite?
AbstractThis 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. © 2007 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/71257
ISSN
2023 Impact Factor: 5.7
2023 SCImago Journal Rankings: 1.897
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorSze, NNen_HK
dc.contributor.authorWong, SCen_HK
dc.date.accessioned2010-09-06T06:30:21Z-
dc.date.available2010-09-06T06:30:21Z-
dc.date.issued2007en_HK
dc.identifier.citationAccident Analysis And Prevention, 2007, v. 39 n. 6, p. 1267-1278en_HK
dc.identifier.issn0001-4575en_HK
dc.identifier.urihttp://hdl.handle.net/10722/71257-
dc.description.abstractThis 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. © 2007 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier Ltd. The Journal's web site is located at http://www.elsevier.com/wps/find/journaldescription.cws_home/336/description#descriptionen_HK
dc.relation.ispartofAccident Analysis and Preventionen_HK
dc.subjectBinary logistic regression-
dc.subjectHosmer-Lemeshow statistic-
dc.subjectInjury severity-
dc.subjectInteraction effect-
dc.subjectLogistic regression diagnostics-
dc.subjectPedestrian casualty-
dc.subject.meshAccidents, Traffic - mortality - statistics & numerical dataen_HK
dc.subject.meshAdolescenten_HK
dc.subject.meshAdulten_HK
dc.subject.meshAgeden_HK
dc.subject.meshChilden_HK
dc.subject.meshChild, Preschoolen_HK
dc.subject.meshFemaleen_HK
dc.subject.meshHong Kong - epidemiologyen_HK
dc.subject.meshHumansen_HK
dc.subject.meshLogistic Modelsen_HK
dc.subject.meshMaleen_HK
dc.subject.meshMiddle Ageden_HK
dc.subject.meshRisk Assessment - statistics & numerical dataen_HK
dc.subject.meshTrauma Severity Indicesen_HK
dc.subject.meshWalking - injuriesen_HK
dc.subject.meshWounds and Injuries - mortalityen_HK
dc.titleDiagnostic analysis of the logistic model for pedestrian injury severity in traffic crashesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0001-4575&volume=39&spage=1267&epage=1278&date=2007&atitle=Diagnostic+analysis+of+the+logistic+model+for+pedestrian+injury+severity+in+traffic+crashesen_HK
dc.identifier.emailWong, SC:hhecwsc@hku.hken_HK
dc.identifier.authorityWong, SC=rp00191en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.aap.2007.03.017en_HK
dc.identifier.pmid17920851-
dc.identifier.scopuseid_2-s2.0-34848909556en_HK
dc.identifier.hkuros138442en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34848909556&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume39en_HK
dc.identifier.issue6en_HK
dc.identifier.spage1267en_HK
dc.identifier.epage1278en_HK
dc.identifier.isiWOS:000250892000025-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridSze, NN=8412831200en_HK
dc.identifier.scopusauthoridWong, SC=24323361400en_HK
dc.identifier.citeulike2851431-
dc.identifier.issnl0001-4575-

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