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Estimating driver crash risks based on the extended Bradley–Terry model: an induced exposure method

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  • Lel Li
  • Karl Kim

Abstract

Quantifying driver crash risks has been difficult because the exposure data are often incompatible with crash frequency data. Induced exposure methods provide a promising idea that a relative measurement of driver crash risks can be derived solely from crash frequency data. This paper describes an application of the extended Bradley–Terry model for paired preferences to estimating driver crash risks. We estimate the crash risk for driver groups defined by driver–vehicle characteristics from log‐linear models in terms of a set of relative risk scores by using only crash frequency data. Illustrative examples using police‐reported crash data from Hawaii are presented.

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  • Lel Li & Karl Kim, 2000. "Estimating driver crash risks based on the extended Bradley–Terry model: an induced exposure method," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(2), pages 227-240.
    • Handle: RePEc:bla:jorssa:v:163:y:2000:i:2:p:227-240
    DOI: 10.1111/1467-985X.00167
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    Cited by:

    1. Frits Bijleveld & Jacques Commandeur & Phillip Gould & Siem Jan Koopman, 2008. "Model‐based measurement of latent risk in time series with applications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 265-277, January.

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