Use of Bivariate Random-Parameter Probit Model to Analyze the Injury Severity of Highway Traffic Crashes Involving School-Age Children

Lee, Jae Young; Mao, Suyi; Abdel-Aty, Mohamed; Wen, Fu Qiang

doi:10.1177/03611981211011620

Cited by 9 publications

(3 citation statements)

References 34 publications

(64 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where the correlation coefficient, rho ( ρ ), is the cross-equation error term indicating the common unobserved correlated factors ( 40 ). In the current study, ρ estimates the correlation between correct child restraint use and correct seating position of a child passenger after the effects of the independent variables in the model are accounted for.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Child Restraint Use and Seating Position of Child Passengers in Motor Vehicles and Their Correlations: Application of a Random-Effects Bivariate Probit Model

Chakraborty

Mahmud

Gates

2022

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

Motor vehicle crashes are a leading cause of death and injury for children aged under 8 years. In the U.S.A., while some states are showing increases in the proportion of child restraint device use, only around half of child passengers aged from 4 to 7 years are being properly restrained. This study was undertaken to identify the factors contributing to the proper child restraint use and child passenger’s seating position through the direct observation surveys of more than 10,000 child passengers in 2015 and 2018 in Michigan. A bivariate probit model with random effects was developed to identify simultaneously the contributing factors for the proper restraint use and seating position of child passengers, accounting for the unobserved heterogeneity in the data. The bivariate framework is able to account for the correlation of the two dependent variables in the study. The results show that the two dependent variables are positively correlated, and this correlation is strongly significant. The key factors simultaneously influencing proper child restraint use and appropriate seating position of the child passenger include the age of the child, the number of child passengers in the vehicle, driver belt use, driver gender, age, and race, vehicle type, stratum, weather, and the time of the day and week. However, factors such as county-specific population, income, and education, and the type of location did not have any significant association with either child restraint use or the seating position of the child passenger.

show abstract

Section: Methodsmentioning

confidence: 99%

“…where β jk is the mean of the coefficient and ε ijk is a normally distributed disturbance or error term with a mean of zero and variance σ 2 ( 40 ).…”

Section: Methodsmentioning

confidence: 99%

Child Restraint Use and Seating Position of Child Passengers in Motor Vehicles and Their Correlations: Application of a Random-Effects Bivariate Probit Model

Chakraborty

Mahmud

Gates

2022

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

show abstract

“…However, the heterogeneity of unobserved factors, independence of irrelevant alternatives, correlation of error terms and other limitations from the abovementioned models all could result in a biased estimation. Therefore, nested logit model [21,22], random parameter model [23], random effect model [24], latent class model [25], multivariate logit/probit model [26] and other mixed models were utilized to eliminate different limitations so that realized the more accurate estimation. Russo et al, proposed a random parameter ordered model for the analysis of passengers' injury severity, which took into account the potential correlation of passengers in a traffic crash and the unobserved heterogeneity [27].…”

Section: Modeling Injury Severity In Traffic Crashesmentioning

confidence: 99%

Relationship between Vehicle Safety Ratings and Drivers’ Injury Severity in the Context of Gender Disparity

Wen

Lee

2022

IJERPH

Self Cite

View full text Add to dashboard Cite

Previous studies have analyzed the relationship between vehicle safety ratings from impact tests and actual crash injury severity. Nevertheless, no study has investigated the relationship in the context of gender disparity. The main objective of this paper is to explore the validity of the 5-star ratings of the U.S. National Highway Traffic Safety Administration, which describes vehicles’ protectiveness, using actual traffic crash data by gender. Random parameter models are developed using 2015–2020 two-vehicle crash data from Maryland, United States. According to the data, over 90% of vehicles have 4–5 stars in overall, front-impact, and side-impact 5-star ratings. After controlling other factors, it is shown that woman drivers are more likely to be seriously injured in two-vehicle crashes than men drivers when using vehicles with the same 5-star safety ratings. Moreover, there is significant individual heterogeneity in the effect of vehicles with different 5-star safety ratings on driver injury severity. Using vehicles with more stars can reduce the risk of being seriously injured for most man drivers. However, the probability of woman drivers being seriously injured is reduced by approximately 5% on average by using vehicles with higher star ratings in the overall and front-impact 5-star rating, and individual heterogeneity shows a difference of nearly 50% in positive and negative effects. The overall and front-impact 5-star ratings of vehicles could not provide reasonable information as the safety performance of vehicles in traffic crashes for woman drivers. On the other hand, drivers’ residence, driving characteristics, crash types, and environmental characteristics are significantly associated with the injury severity. It is expected that the results from this study will contribute to guide a better vehicle safety design for both men and women.

show abstract

Exploring the influence of drivers’ visual surroundings on speeding behavior

Abdel-Aty,

Ugan,

Islam

2024

Accident Analysis & Prevention

View full text Add to dashboard Cite

Use of Bivariate Random-Parameter Probit Model to Analyze the Injury Severity of Highway Traffic Crashes Involving School-Age Children

Cited by 9 publications

References 34 publications

Child Restraint Use and Seating Position of Child Passengers in Motor Vehicles and Their Correlations: Application of a Random-Effects Bivariate Probit Model

Child Restraint Use and Seating Position of Child Passengers in Motor Vehicles and Their Correlations: Application of a Random-Effects Bivariate Probit Model

Relationship between Vehicle Safety Ratings and Drivers’ Injury Severity in the Context of Gender Disparity

Exploring the influence of drivers’ visual surroundings on speeding behavior

Contact Info

Product

Resources

About