Analysis of Traffic Injury Crash Proportions Using Geographically Weighted Beta Regression

Author:

da Silva Alan Ricardo1ORCID,Buffone Roberto de Souza Marques1

Affiliation:

1. Departamento de Estatística, Universidade de Brasilia, Campus Universitário Darcy Ribeiro, Prédio CIC/EST Sala A1 35/28, Asa Norte, Brasília 70910-900, DF, Brazil

Abstract

The classical linear regression model allows for a continuous quantitative variable to be modeled simply from other variables. However, this model assumes independence between observations, which, if ignored, can lead to methodological issues. Additionally, not all data follow a normal distribution, prompting the need for alternative modeling methods. In this context, geographically weighted beta regression (GWBR) incorporates spatial dependence into the modeling process and analyzes rates or proportions using the beta distribution. In this study, GWBR was applied to the traffic injury (fatal and non-fatal) crash proportions in Fortaleza, Ceará, Brazil, from 2009 to 2011. The results demonstrated that the local approach using the beta distribution is a viable model for explaining the traffic injury crash proportions, due to its flexibility in handling both symmetric and skewed distributions. Therefore, when analyzing rates or proportions, the use of the GWBR model is recommended.

Funder

National Council for Scientific and Technological Development

Publisher

MDPI AG

Reference43 articles.

1. Vision zero—Implementing a policy for traffic safety;Johansson;Saf. Sci.,2009

2. Vision Zero Network (2022, November 11). What Is Vision Zero?. Available online: https://visionzeronetwork.org/about/what-is-vision-zero/.

3. World Health Organization (2024, April 28). Decade of Action for Road Safety 2021–2030. Available online: https://www.who.int/teams/social-determinants-of-health/safety-and-mobility/decade-of-action-for-road-safety-2021-2030.

4. Institute for Health Metrics and Evaluation (2022, December 29). Global Burden of Disease. Available online: https://ghdx.healthdata.org/gbd-2019.

5. World Health Organization (2022, December 26). WHO Mortality Database—Road Traffic Accidents. Available online: https://platform.who.int/mortality/themes/theme-details/topics/indicator-groups/indicator-group-details/MDB/road-traffic-accidents.

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