A bivariate random effects spatial model of traffic fatalities and injuries across Provinces of Iran

Besharati, Mohammad Mehdi; Kashani, Ali Tavakoli; Li, Zili; Washington, Simon; Prato, Carlo Giacomo

doi:10.1016/j.aap.2019.105394

Cited by 13 publications

(14 citation statements)

References 34 publications

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“…Taken both within-crash correlation and unobserved heterogeneity into consideration, the proposed model outperformed the individual ordered probit models with fixed parameters, which provides the foundation for this study. A recent study by Besharati et al [28] extended into a bivariate spatial negative binomial Bayesian model with random effects of traffic fatalities and injuries across Provinces of Iran. Unobserved heterogeneity and spatial correlation were addressed, and the results helped to prioritize area-wide safety initiatives and programs.…”

Section: Introductionmentioning

confidence: 99%

Insights on Crash Injury Severity Control from Novice and Experienced Drivers: A Bivariate Random-Effects Probit Analysis

Xiao

Yuan

Kang

et al. 2021

Discrete Dynamics in Nature and Society

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This study intended to investigate the crash injury severity from the insights of the novice and experienced drivers. To achieve this objective, a bivariate panel data probit model was initially proposed to account for the correlation between both time-specific and individual-specific error terms. The geocrash data of Las Vegas metropolitan area from 2014 to 2017 were collected. In order to estimate two (seemingly unrelated) nonlinear processes and to control for interrelations between the unobservables, the bivariate random-effects probit model was built up, in which injury severity levels of novice and experienced drivers were addressed by bivariate (seemingly unrelated) probit simultaneously, and the interrelations between the unobservables (i.e., heterogeneity issue) were accommodated by bivariate random-effects model. Results revealed that crash types, vehicle types of minor responsibility, pedestrians, and motorcyclists were potentially significant factors of injury severity for novice drivers, while crash types, driver condition of minor responsibility, first harm, and highway factor were significant for experienced drivers. The findings provide useful insights for practitioners to improve traffic safety levels of novice and experienced drivers.

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Section: Introductionmentioning

confidence: 99%

Insights on Crash Injury Severity Control from Novice and Experienced Drivers: A Bivariate Random-Effects Probit Analysis

Xiao

Yuan

Kang

et al. 2021

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

show abstract

“…The development of joint spatial and spatiotemporal methodologies has coincided with a huge advancement in statistical approaches addressing technical and statistical issues related to advanced spatial statistics. For example, authors employed different Bayesian inference techniques such as Markov chain Monte Carlo (MCMC) [ 32 , 33 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 ] or Integrated Nested Laplace Approximation (INLA) methods [ 42 , 43 , 61 , 62 , 63 , 64 , 65 ] in Bayesian shared component spatial and spatiotemporal models.…”

Section: Introductionmentioning

confidence: 99%

A Systematic Review of Joint Spatial and Spatiotemporal Models in Health Research

Tesema

Tessema

Héritier

et al. 2023

IJERPH

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With the advancement of spatial analysis approaches, methodological research addressing the technical and statistical issues related to joint spatial and spatiotemporal models has increased. Despite the benefits of spatial modelling of several interrelated outcomes simultaneously, there has been no published systematic review on this topic, specifically when such models would be useful. This systematic review therefore aimed at reviewing health research published using joint spatial and spatiotemporal models. A systematic search of published studies that applied joint spatial and spatiotemporal models was performed using six electronic databases without geographic restriction. A search with the developed search terms yielded 4077 studies, from which 43 studies were included for the systematic review, including 15 studies focused on infectious diseases and 11 on cancer. Most of the studies (81.40%) were performed based on the Bayesian framework. Different joint spatial and spatiotemporal models were applied based on the nature of the data, population size, the incidence of outcomes, and assumptions. This review found that when the outcome is rare or the population is small, joint spatial and spatiotemporal models provide better performance by borrowing strength from related health outcomes which have a higher prevalence. A framework for the design, analysis, and reporting of such studies is also needed.

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“…In other words, relaxing speed limits undermines traffic safety, giving rise to fatal and injury crashes [7][8][9][10]. Besharati et al [11] suggested that both fatal and nonfatal injuries can be reduced significantly by installing more speed cameras over rural roads. Abdel-Aty et al [12] evaluated how different variable speed limits (VSLs) improve the traffic safety on roads.…”

Section: Introductionmentioning

confidence: 99%

Influencing Factors for Illegal Driving Behaviors of Rural Bus Drivers

Xiao¹,

Liang²

2020

IJSSE

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To improve the safety management of rural buses, this paper attempts to identify the factors affecting the drivers' behavioral features and their illegal driving behaviors. From the perspective of driver psychology, the safety incentive (SI) index was introduced to improve the theory of planned behavior (TPB) model. Then, the authors verified the improved TPB model for the illegal driving behaviors of rural bus drivers. In addition, the influence mechanisms of several factors on the illegal driving behaviors were fully analyzed, namely, attitude toward the behavior (AB), subjective norm (SN), perceived behavioral control (PBC), and the SI. The results show that the rural bus drivers have not developed a correct understanding of illegal driving behaviors; the attitudes of families, friends and passengers can indirectly affect the driving behaviors; the PBC of the driver has a direct or an indirect influence on the illegal driving behaviors; the SI, as the additional index, has a significant inhibitory effect on illegal driving behaviors. Finally, it is advised to improve the safety management of rural buses by improving education and publicity, supervising the whole driving process, and perfecting the SI system.

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A bivariate random effects spatial model of traffic fatalities and injuries across Provinces of Iran

Cited by 13 publications

References 34 publications

Insights on Crash Injury Severity Control from Novice and Experienced Drivers: A Bivariate Random-Effects Probit Analysis

Insights on Crash Injury Severity Control from Novice and Experienced Drivers: A Bivariate Random-Effects Probit Analysis

A Systematic Review of Joint Spatial and Spatiotemporal Models in Health Research

Influencing Factors for Illegal Driving Behaviors of Rural Bus Drivers

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