JSM 2011 Online Program

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Abstract Details

Activity Number: 651
Type: Topic Contributed
Date/Time: Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
Sponsor: Social Statistics Section
Abstract - #302301
Title: Temporal Modeling Of Highway Crash Severity By Involved Person Age
Author(s): Shan Hu and James Mooradian*+ and Nalini Ravishanker and John Ivan
Companies: University of Connecticut and University of Connecticut and University of Connecticut
Address: Department of Civil and Environmental Engineering, Storrs, CT, 06269,
Keywords: Hierarchical generalized linear models ; Predictive dynamic time series models
Abstract:

This project uses dynamic time series models to uncover temporal patterns in the severity level (fatal, serious injury, minor injury, slight injury and no injury) for persons involved in highway crashes in Connecticut. Existing state sources provide data describing the time and weather conditions for each crash and the vehicles and persons involved over the time period from 1995 to 2008 as well as the traffic volumes and the characteristics of the roads on which these crashes occurred. Controlling for characteristics known to be related to severity, e.g., age, gender, and road characteristics, statistical modeling enables us to predict the likelihood of an individual to have a specific severity outcome if he/she is involved in a highway crash, as well as to identify trends in the crash outcomes for senior motor vehicle travelers (65 years and over) that point to significant impacts on public health and safety as the elderly become a larger portion of the population.


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