Addressing unobserved heterogeneity in the analysis of bicycle crash injuries in Scotland: A correlated random parameters ordered probit approach with heterogeneity in means-Reference-Cited by-同舟云学术

Addressing unobserved heterogeneity in the analysis of bicycle crash injuries in Scotland: A correlated random parameters ordered probit approach with heterogeneity in means

Published:2021-12 Issue: Volume:32 Page:100181
ISSN:2213-6657
Container-title:Analytic Methods in Accident Research
language:en
Short-container-title:Analytic Methods in Accident Research

Author:

Fountas Grigorios^ORCID,Fonzone Achille^ORCID,Olowosegun Adebola^ORCID,McTigue Clare^ORCID

Funder

Edinburgh Napier University

Publisher

Elsevier BV

Subject

Safety Research,Transportation

Reference71 articles.

1. Analysis of safety benefits and security concerns from the use of autonomous vehicles: A grouped random parameters bivariate probit approach with heterogeneity in means;Ahmed;Analytic Methods in Accident Research,2020

3. Temporal stability of driver injury severities in animal-vehicle collisions: A random parameters with heterogeneity in means (and variances) approach;Al-Bdairi;Analytic Methods in Accident Research,2020

4. The effect of speed limits on drivers’ choice of speed: a random parameters seemingly unrelated equations approach;Anastasopoulos;Analytic Methods in Accident Research,2016

5. Non-decreasing threshold variances in mixed generalized ordered response models: A negative correlations approach to variance reduction;Balusu;Analytic Methods in Accident Research,2018

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