Exploring injury severity in head-on crashes using latent class clustering analysis and mixed logit model: A case study of North Carolina

Accident Analysis and Prevention

Volumn 135, Issue , 2020, Pages

  Liu, Pengfei ^a   Fan, Wei ^a  

^a University of North Carolina at Charlotte   (United States)

Author keywords

Head on crashes; Latent class clustering; Mixed logit model; Severity analysis

Indexed keywords

HIGHWAY ENGINEERING;

CLUSTERING ANALYSIS; CONTRIBUTING FACTOR; HEAD-ON CRASHES; LATENT CLASS; MIXED LOGIT MODELS; SEVERITY ANALYSIS; SIGNIFICANT VARIABLES; UNOBSERVED HETEROGENEITY;

ACCIDENTS;

ADULT; DRUNKEN DRIVING; FEMALE; HUMAN; INJURY; INJURY SCALE; LATENT CLASS ANALYSIS; MALE; MIDDLE AGED; MORTALITY; NORTH CAROLINA; STATISTICAL MODEL; TRAFFIC ACCIDENT; UNITED STATES; YOUNG ADULT;

ACCIDENTS, TRAFFIC; ADULT; DRIVING UNDER THE INFLUENCE; FEMALE; HUMANS; INJURY SEVERITY SCORE; LATENT CLASS ANALYSIS; LOGISTIC MODELS; MALE; MIDDLE AGED; NORTH CAROLINA; UNITED STATES; WOUNDS AND INJURIES; YOUNG ADULT;

EID: 85077298405     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2019.105388     Document Type: Article

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