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Identifying Temporal Aggregation Effect on Crash-Frequency Modeling

Author

Listed:
  • Bumjoon Bae

    (Center for Privately-Financed Highway Studies, The Korea Transport Institute, Sejong 30147, Korea)

  • Changju Lee

    (Environment, Planning and Economic Division, Virginia Transportation Research Council, Charlottesville, VA 22904, USA
    Current Affiliation: Transport Division, United Nations Economic and Social Commission for Asia and the Pacific, Bangkok 10200, Thailand.)

  • Tae-Young Pak

    (Department of Consumer Science, Sungkyunkwan University, Seoul 03063, Korea)

  • Sunghoon Lee

    (Business Data Analytics Team, Samsung Card Co., Ltd., Seoul 04514, Korea)

Abstract

Aggregation of spatiotemporal data can encounter potential information loss or distort attributes via individual observation, which would influence modeling results and lead to an erroneous inference, named the ecological fallacy. Therefore, deciding spatial and temporal resolution is a fundamental consideration in a spatiotemporal analysis. The modifiable temporal unit problem (MTUP) occurs when using data that is temporally aggregated. While consideration of the spatial dimension has been increasingly studied, the counterpart, a temporal unit, is rarely considered, particularly in the traffic safety modeling field. The purpose of this research is to identify the MTUP effect in crash-frequency modeling using data with various temporal scales. A sensitivity analysis framework is adopted with four negative binomial regression models and four random effect negative binomial models having yearly, quarterly, monthly, and weekly temporal units. As the different temporal unit was applied, the result of the model estimation also changed in terms of the mean and significance of the parameter estimates. Increasing temporal correlation due to using the small temporal unit can be handled with the random effect models.

Suggested Citation

  • Bumjoon Bae & Changju Lee & Tae-Young Pak & Sunghoon Lee, 2021. "Identifying Temporal Aggregation Effect on Crash-Frequency Modeling," Sustainability, MDPI, vol. 13(11), pages 1-10, May.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:11:p:6214-:d:566615
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    References listed on IDEAS

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    2. Lord, Dominique & Mannering, Fred, 2010. "The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 291-305, June.
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    Cited by:

    1. Bae, Bumjoon & Seo, Changbeom, 2022. "Do public-private partnerships help improve road safety? Finding empirical evidence using panel data models," Transport Policy, Elsevier, vol. 126(C), pages 336-342.

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