Multivariate statistical analysis for exploring road crash-related factors in the Franche-Comté region of France

Q4 Mathematics
Cécile Spychala, Joël Armand, C. Dombry, C. Goga
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引用次数: 1

Abstract

Abstract Understanding and modeling road crash data is crucial in fulfilling safety goals by helping national authorities to take necessary measures to reduce crash frequency and severity. This work aims at giving a multivariate statistical analysis of road crash data from the French region of Franche-Comté with special attention to road crash gravity. The first step for this multivariate analysis was to perform multiple correspondence analysis in order to assess associations between the road crash injury and several important accident-related factors and circumstances. Log-linear models are used next in order to detect associations between road crash severity and related factors such as alcohol/drug consumption or spatial crash locations. The effects of each factors have been also evaluated on the road crash gravity by using ordinal logistic regression. Data used in this study are extracted from BAAC files, the French census of road crashes.
探讨法国弗朗什-康涅斯地区道路交通事故相关因素的多元统计分析
通过帮助国家当局采取必要措施减少碰撞频率和严重程度,理解和建模道路碰撞数据对于实现安全目标至关重要。这项工作旨在对来自法国弗朗什-康涅格地区的道路碰撞数据进行多元统计分析,特别关注道路碰撞重力。这个多变量分析的第一步是进行多重对应分析,以评估道路交通事故伤害与几个重要的事故相关因素和情况之间的联系。接下来使用对数线性模型来检测道路碰撞严重程度与酒精/药物消耗或空间碰撞位置等相关因素之间的关联。利用有序逻辑回归分析了各因素对道路碰撞重力的影响。本研究中使用的数据来自法国道路交通事故普查BAAC文件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.00
自引率
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发文量
29
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