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Characteristics of Cyclist Crashes Using Polytomous Latent Class Analysis and Bias-Reduced Logistic Regression

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  • Yuta Sekiguchi

    (Graduate School of Science and Engineering, Chuo University, Tokyo 112-8551, Japan)

  • Masayoshi Tanishita

    (Department of Civil and Environmental Engineering, Chuo University, Tokyo 112-8551, Japan)

  • Daisuke Sunaga

    (Department of Civil and Environmental Engineering, Chuo University, Tokyo 112-8551, Japan)

Abstract

Although the number of cyclist crashes is decreasing in Japan, the fatality rate is not. Thus, reducing their severity is a major challenge. We used a polytomous latent class analysis to understand their characteristics and bias-reduced logistic regression to analyze their severity. Specifically, 90,696 combinations and 139,955 cyclist accidents were divided into 17 classes. The variable contributing the most to the classification was the crash location. Common fatality risks included older age groups and rural areas, whereas other factors differed among crash locations. Median strips, stop signs, and boundaries between the sidewalk and roadway affected the severity of crashes at intersections. Moreover, the existence of a median strip, collision partner, and time period affected the severity of crashes between intersections. On the sidewalks, the fatality risk was higher when the front part of the bicycle was subjected to the collision.

Suggested Citation

  • Yuta Sekiguchi & Masayoshi Tanishita & Daisuke Sunaga, 2022. "Characteristics of Cyclist Crashes Using Polytomous Latent Class Analysis and Bias-Reduced Logistic Regression," Sustainability, MDPI, vol. 14(9), pages 1-15, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5497-:d:807947
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    References listed on IDEAS

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    1. Linzer, Drew A. & Lewis, Jeffrey B., 2011. "poLCA: An R Package for Polytomous Variable Latent Class Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i10).
    2. Ioannis Kosmidis & David Firth, 2021. "Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models," Biometrika, Biometrika Trust, vol. 108(1), pages 71-82.
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    Cited by:

    1. Masayoshi Tanishita & Yuta Sekiguchi, 2023. "Impact Analysis of Road Infrastructure and Traffic Control on Injury Severity of Single- and Multi-Vehicle Crashes," Sustainability, MDPI, vol. 15(17), pages 1-17, September.
    2. Kun Wang & Xiaoyuan Feng & Hongbo Li & Yilong Ren, 2022. "Exploring Influential Factors Affecting the Severity of Urban Expressway Collisions: A Study Based on Collision Data," IJERPH, MDPI, vol. 19(14), pages 1-11, July.

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