2017
DOI: 10.1016/j.jtte.2016.08.003
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Factors associated with crash severities in built-up areas along rural highways of Nevada: A case study of 11 towns

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Cited by 18 publications
(6 citation statements)
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“…Hereafter, the theoretical basis of this statistical method is detailed. The equation of the linear function Q that determines the injury output i for observation n can be defined as follows: (5) where I is a vector of computable coefficients, Xin is a vector of discernible features that affect the driver injury severity sustained by observation n. in is an alteration term that takes into account the no observed effects. In those cases, in which these alteration terms can be distributed independently and are equal to the generalized distribution of extreme values, the model can be represented with the following expression [49]:…”
Section: Severity Modelmentioning
confidence: 99%
“…Hereafter, the theoretical basis of this statistical method is detailed. The equation of the linear function Q that determines the injury output i for observation n can be defined as follows: (5) where I is a vector of computable coefficients, Xin is a vector of discernible features that affect the driver injury severity sustained by observation n. in is an alteration term that takes into account the no observed effects. In those cases, in which these alteration terms can be distributed independently and are equal to the generalized distribution of extreme values, the model can be represented with the following expression [49]:…”
Section: Severity Modelmentioning
confidence: 99%
“…The study by Li, Song, and Fan (2021) have explained the likelihood of the increased odds of fatal head-on crashes during weekends. Also, another study by Shrestha and Shrestha (2017) showed that crashes on weekdays were three times more likely to be injury crashes than on weekends.…”
Section: Day Of the Weekmentioning
confidence: 99%
“…Researchers have employed many statistical techniques to analyze driver injury severity. Among these techniques were multinomial logit, nested logit, ordered logit, probit models, and binary logistic regression [5,[20][21][22][23][24][25][26]. The BLR can be mathematically expressed as in the following the equation:…”
Section: Data Analysis By Binary Logistic Regression Modelmentioning
confidence: 99%