Literature DB >> 18329439

Modeling motor vehicle crashes for street racers using zero-inflated models.

Zhuo Li1, Stacey Knight, Lawrence J Cook, Lisa K Hyde, Richard Holubkov, Lenora M Olson.   

Abstract

Motor vehicle crashes are a leading cause of death for young people in the United States. Assessing which drivers are at a high risk of experiencing a crash is important for the implementation of traffic regulations. Illegal street racing has been associated with a high rate of motor vehicle crashes. In this study, we link Utah statewide driver license citations and motor vehicle crash data to evaluate the rate of crashes for drivers with street racing citations relative to other drivers. Using a zero-inflated negative binomial model we found that drivers with no citations are approximately three times more likely to be at zero risk of a crash compared to drivers with street racing citations. Moreover, among drivers at non-negligible risk of crash, cited street racers are more likely to be involved in a crash compared to drivers without citations or those cited for violations other than street racing. However, drivers with increased numbers of non-street-racing citations experience crash risks approaching those of the cited street racers.

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Year:  2007        PMID: 18329439     DOI: 10.1016/j.aap.2007.09.022

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  2 in total

1.  U.S. Adolescent Street Racing and Other Risky Driving Behaviors.

Authors:  Indra Neal Kar; Chantal Guillaume; Kellienne R Sita; Pnina Gershon; Bruce G Simons-Morton
Journal:  J Adolesc Health       Date:  2018-05       Impact factor: 5.012

2.  Risk factor analysis and spatiotemporal CART model of cryptosporidiosis in Queensland, Australia.

Authors:  Wenbiao Hu; Kerrie Mengersen; Shilu Tong
Journal:  BMC Infect Dis       Date:  2010-10-28       Impact factor: 3.090

  2 in total

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