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- W787061299 abstract "This paper describes analysis using ordinal logistic regression to uncover temporal patterns in the severity level (fatal, serious injury, minor injury, slight injury or 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, crash type, and road characteristics, statistical modeling enables us to predict the probability of an individual to have a specific severity outcome if he/she is involved in a crash. Specifically, this paper investigates overall, long-term, time dependant and seasonal trends in senior drivers and travelers (65 years and over). This study also accounts for special conditions in data distribution and modeling in order to point to significant impacts on public health and safety as seniors become a larger portion of the population. Findings indicate an overall increase in increased crash severity probability for seniors, as well as a distinct seasonal trend. Other time-dependant trends in the data were visible, but not significant." @default.
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- W787061299 date "2012-01-01" @default.
- W787061299 modified "2023-09-23" @default.
- W787061299 title "Temporal Modeling of Highway Crash Severity for Seniors and Other Involved Persons" @default.
- W787061299 hasPublicationYear "2012" @default.
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