Literature DB >> 21658493

The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives.

Peter T Savolainen1, Fred L Mannering, Dominique Lord, Mohammed A Quddus.   

Abstract

Reducing the severity of injuries resulting from motor-vehicle crashes has long been a primary emphasis of highway agencies and motor-vehicle manufacturers. While progress can be simply measured by the reduction in injury levels over time, insights into the effectiveness of injury-reduction technologies, policies, and regulations require a more detailed empirical assessment of the complex interactions that vehicle, roadway, and human factors have on resulting crash-injury severities. Over the years, researchers have used a wide range of methodological tools to assess the impact of such factors on disaggregate-level injury-severity data, and recent methodological advances have enabled the development of sophisticated models capable of more precisely determining the influence of these factors. This paper summarizes the evolution of research and current thinking as it relates to the statistical analysis of motor-vehicle injury severities, and provides a discussion of future methodological directions.
Copyright © 2011 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 21658493     DOI: 10.1016/j.aap.2011.03.025

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  28 in total

1.  Pedestrian injuries-related deaths: a global evaluation.

Authors:  Hani O Eid; Fikri M Abu-Zidan
Journal:  World J Surg       Date:  2015-03       Impact factor: 3.352

2.  Distraction-related road traffic collisions.

Authors:  Hani O Eid; Fikri M Abu-Zidan
Journal:  Afr Health Sci       Date:  2017-06       Impact factor: 0.927

3.  Application of Extremely Randomised Trees for exploring influential factors on variant crash severity data.

Authors:  Farshid Afshar; Seyedehsan Seyedabrishami; Sara Moridpour
Journal:  Sci Rep       Date:  2022-07-07       Impact factor: 4.996

4.  Impacts of confounding roadway characteristics on estimates of associations between alcohol outlet densities and alcohol-related motor vehicle crashes.

Authors:  Robert Lipton; Aniruddha Banerjee; William R Ponicki; Paul J Gruenewald; Christopher Morrison
Journal:  Drug Alcohol Rev       Date:  2020-08-26

5.  A semi-nonparametric Poisson regression model for analyzing motor vehicle crash data.

Authors:  Xin Ye; Ke Wang; Yajie Zou; Dominique Lord
Journal:  PLoS One       Date:  2018-05-23       Impact factor: 3.240

6.  Characteristic Analysis of Unsafe Behavior by Coal Miners: Multi-Dimensional Description of the Pan-Scene Data.

Authors:  Ruipeng Tong; Yanwei Zhang; Pengcheng Cui; Cunli Zhai; Meng Shi; Surui Xu
Journal:  Int J Environ Res Public Health       Date:  2018-07-29       Impact factor: 3.390

7.  A Normal Distribution-Based Methodology for Analysis of Fatal Accidents in Land Hazardous Material Transportation.

Authors:  Cuiping Ren; Qunqi Wu; Chunguo Zhang; Shengzhong Zhang
Journal:  Int J Environ Res Public Health       Date:  2018-07-07       Impact factor: 3.390

8.  Long-lasting virtual motorcycle-riding trainer effectiveness.

Authors:  Giulio Vidotto; Mariaelena Tagliabue; Michael D Tira
Journal:  Front Psychol       Date:  2015-10-29

9.  Determination of the Risk Factors That Influence Occurrence Time of Traffic Accidents with Survival Analysis.

Authors:  Burcu Oralhan; Ziya Gökalp Göktolga
Journal:  Iran J Public Health       Date:  2018-08       Impact factor: 1.429

10.  A novel rare event approach to measure the randomness and concentration of road accidents.

Authors:  Rafael Prieto Curiel; Humberto González Ramírez; Steven Richard Bishop
Journal:  PLoS One       Date:  2018-08-08       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.