Analyzing freeway crash severity using a Bayesian spatial generalized ordered logit model with conditional autoregressive priors-Reference-Cited by-同舟云学术

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Analyzing freeway crash severity using a Bayesian spatial generalized ordered logit model with conditional autoregressive priors

Published:2019-06 Issue: Volume:127 Page:87-95
ISSN:0001-4575
Container-title:Accident Analysis & Prevention
language:en
Short-container-title:Accident Analysis & Prevention

Author:

Zeng Qiang,Gu Weihua,Zhang Xuan,Wen Huiying,Lee Jinwoo,Hao Wei

Funder

the Hong Kong Polytechnic University research fund

Natural Science Foundation of China

National Key R&D Program of China

Natural Science Foundation of Guangdong Province

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Safety, Risk, Reliability and Quality,Human Factors and Ergonomics

Reference70 articles.

1. Analysis of driver injury severity levels at multiple locations using ordered probit models;Abdel-Aty;J. Saf. Res.,2003

2. Effects of excessive speeding and falling asleep while driving on crash injury severity in Ethiopia: a generalized ordered logit model analysis;Abegaz;Accid. Anal. Prev.,2014

3. Exploring a bayesian hierarchical approach for developing safety performance functions for a mountainous freeway;Ahmed;Accid. Anal. Prev.,2011

4. A new look at the statistical model identification;Akaike;IEEE Trans. Autom. Control,1974

5. Non-decreasing threshold variances in mixed generalized ordered response models: a negative correlations approach to variance reduction;Balusu;Anal. Methods Accid. Res.,2018

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