Rainfall effect on single-vehicle crash severities using polychotomous response models

Jung, Soyoung; Qin, Xiaoxia; Noyce, David A.

doi:10.1016/j.aap.2009.07.020

Cited by 142 publications

(58 citation statements)

References 28 publications

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“…X k f grepresents a set of explanatory variables. An important aspect of ordered logit models is the proportional odds (or parallel slopes) assumption, where the variables are assumed to have the same slope across all levels of severity/outcome [46][47][48] with the exception of the intercept [49]. Results of ordered logit models are therefore unidirectional (show either an increase or decrease in severity) and are thus very easy to interpret.…”

Section: Multilevel Logistic Regression Modelsmentioning

confidence: 99%

Injury severity analysis: comparison of multilevel logistic regression models and effects of collision data aggregation

Usman

Miranda-Moreno

2016

J. Mod. Transport.

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This paper describes an empirical study aiming at identifying the main differences between different logistic regression models and collision data aggregation methods that are commonly applied in road safety literature for modeling collision severity. In particular, the research compares three popular multilevel logistic models (i.e., sequential binary logit models, ordered logit models, and multinomial logit models) as well as three data aggregation methods (i.e., occupant based, vehicle based, and collision based). Six years of collision data (2001)(2002)(2003)(2004)(2005)(2006) from 31 highway routes from across the province of Ontario, Canada were used for this analysis. It was found that a multilevel multinomial logit model has the best fit to the data than the other two models while the results obtained from occupant-based data are more reliable than those from vehicle-and collision-based data. More importantly, while generally consistent in terms of factors that were found to be significant between different models and data aggregation methods, the effect size of each factor differ substantially, which could have significant implications for evaluating the effects of different safety-related policies and countermeasures.

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Section: Multilevel Logistic Regression Modelsmentioning

confidence: 99%

Injury severity analysis: comparison of multilevel logistic regression models and effects of collision data aggregation

Usman

Miranda-Moreno

2016

J. Mod. Transport.

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“…Our choice of the ordered-response specification for injury severity deserves some explanation here. Many earlier injury severity studies have used such a specification to appropriately recognize the ordinal nature of the injury severity levels (see, for example, Xie et al, 2009, Christoforou et al, 2010, Haleem and Abdel-Aty, 2010, Quddus et al, 2010, Jung et al, 2010, Zhu and Srinivasan, 2011. In recent years, unordered-response specifications have also been considered (see, for example, Rifaat et al, 2011, Yan et al, 2011, Malyshkina and Mannering, 2009, Huang et al, 2008, Milton et al, 2008, Kim et al, 2010, and Moore et al, 2011.…”

Section: Current Study In Contextmentioning

confidence: 99%

“…8 As in earlier safety studies (see, for example, Zhu and Srinivasan, 2011, Rana et al, 2010, Jung et al, 2010, and Huang et al, 2008, we do not consider vehicle make/model in our analysis because it leads to an explosion in the number of model parameters.…”

Section: Exogenous Variablesmentioning

confidence: 99%

The joint analysis of injury severity of drivers in two-vehicle crashes accommodating seat belt use endogeneity

Abay

Paleti

Bhat

2013

Transportation Research Part B: Methodological

107

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The current study contributes to the existing injury severity modeling literature by developing a multivariate probit model of injury severity and seat belt use decisions of both drivers involved in two-vehicle crashes. The modeling approach enables the joint modeling of the injury severity of multiple individuals involved in a crash, while also recognizing the endogeneity of seat belt use in predicting injury severity levels as well as accommodating unobserved heterogeneity in the effects of variables. The proposed model is applied to analyze the injury severity of drivers involved in two-vehicle road crashes in Denmark.The empirical analysis provides strong support for the notion that people offset the restraint benefits of seat belt use by driving more aggressively. Also, men and those individuals driving heavy vehicles have a lower injury risk than women and those driving lighter vehicles, respectively. At the same time, men and individuals driving heavy vehicles pose more of a danger to other drivers on the roadway when involved in a crash. Other important determinants of injury severity include speed limit on roadways where crash occurs, the presence (or absence) of center dividers (median barriers), and whether the crash involves a head-on collision. These and other results are discussed, along with implications for countermeasures to reduce injury severities in crashes. The analysis also underscores the importance of considering injury severity at a crash level, while accommodating seat belt endogeneity effects and unobserved heterogeneity effects.

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“…The response categories are recorded on ordinal scales from lower to higher severity levels (Yamamoto et al, 2008;Huang et al, 2008;Delen et al, 2006;Jung et al, 2010). The distance between adjoining categories is difficult to establish because there are many factors and circumstances that define the physical condition of an accident victim.…”

Section: Introductionmentioning

confidence: 99%

Discrete distributions when modeling the disability severity score of motor victims

Boucher

Santolino

2010

Accident Analysis & Prevention

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Rainfall effect on single-vehicle crash severities using polychotomous response models

Cited by 142 publications

References 28 publications

Injury severity analysis: comparison of multilevel logistic regression models and effects of collision data aggregation

Injury severity analysis: comparison of multilevel logistic regression models and effects of collision data aggregation

The joint analysis of injury severity of drivers in two-vehicle crashes accommodating seat belt use endogeneity

Discrete distributions when modeling the disability severity score of motor victims

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