解决苏格兰自行车碰撞损伤分析中未观察到的异质性:一种具有均值异质性的相关随机参数有序概率方法

IF 12.5 1区 工程技术 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Grigorios Fountas, Achille Fonzone, Adebola Olowosegun, Clare McTigue
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引用次数: 53

摘要

本文通过估计具有均值异质性的相关随机参数有序概率模型,研究了单自行车和自行车-机动车碰撞中损伤严重程度的决定因素。这种建模方法通过捕获随机参数之间的可能相关性和放松随机参数混合分布的均值的固定性质,扩展了传统随机参数的前沿。实证分析基于英国警方车祸报告的公开数据库,该数据库使用了2010年至2018年间苏格兰城市和农村车道上发生的车祸信息。模型估计结果表明,各种碰撞、道路、位置、天气、驾驶员或骑车人的特征对两类碰撞的伤害严重程度都有影响。平均异质性结构允许在统计分析中纳入明显的异质性层,因为随机参数的平均值被发现作为碰撞或驾驶员/骑自行车者特征的函数而变化。随机参数的相关性使得识别道路、位置和环境因素所捕获的未观察特征的复杂相互作用成为可能。总体而言,发现伤害严重程度的决定因素在单自行车和自行车-机动车碰撞之间有所不同,而许多共同的决定因素在大小和标志方面与不同的影响有关。将提出的方法框架与不太复杂的有序概率模型进行比较,表明其在统计拟合、解释能力和预测准确性方面的相对优势,以及在更大程度上捕捉未观察到的异质性的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Addressing unobserved heterogeneity in the analysis of bicycle crash injuries in Scotland: A correlated random parameters ordered probit approach with heterogeneity in means

This paper investigates the determinants of injury severities in single-bicycle and bicycle-motor vehicle crashes by estimating correlated random parameter ordered probit models with heterogeneity in the means. This modeling approach extends the frontier of the conventional random parameters by capturing the likely correlations among the random parameters and relaxing the fixed nature of the means for the mixing distributions of the random parameters. The empirical analysis was based on a publicly available database of police crash reports in the UK using information from crashes occurred on urban and rural carriageways of Scotland between 2010 and 2018. The model estimation results show that various crash, road, location, weather, and driver or cyclist characteristics affect the injury severities for both categories of crashes. The heterogeneity-in-the-means structure allowed the incorporation of a distinct layer of heterogeneity in the statistical analysis, as the means of the random parameters were found to vary as a function of crash or driver/cyclist characteristics. The correlation of the random parameters enabled the identification of complex interactive effects of the unobserved characteristics captured by road, location and environmental factors. Overall, the determinants of injury severities are found to vary between single-bicycle and bicycle-motor vehicle crashes, whereas a number of common determinants are associated with different effects in terms of magnitude and sign. The comparison of the proposed methodological framework with less sophisticated ordered probit models demonstrated its relative benefits in terms of statistical fit, explanatory power and forecasting accuracy as well as its potential to capture unobserved heterogeneity to a greater extent.

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来源期刊
CiteScore
22.10
自引率
34.10%
发文量
35
审稿时长
24 days
期刊介绍: Analytic Methods in Accident Research is a journal that publishes articles related to the development and application of advanced statistical and econometric methods in studying vehicle crashes and other accidents. The journal aims to demonstrate how these innovative approaches can provide new insights into the factors influencing the occurrence and severity of accidents, thereby offering guidance for implementing appropriate preventive measures. While the journal primarily focuses on the analytic approach, it also accepts articles covering various aspects of transportation safety (such as road, pedestrian, air, rail, and water safety), construction safety, and other areas where human behavior, machine failures, or system failures lead to property damage or bodily harm.
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