Estimating Safety by the Empirical Bayes Method: A Tutorial

  • Ezra Hauer
    35 Merton Street, Apt. 1706, Toronto, Ontario M4S 3G4, Canada
  • Douglas W. Harwood
    Midwest Research Institute, 425 Volker Boulevard, Kansas City, MO 64110
  • Forrest M. Council
    Highway Safety Research Center, University of North Carolina, 730 Airport Road, Chapel Hill, NC 27599-3430
  • Michael S. Griffith
    Federal Highway Administration, Turner-Fairbank Highway Research Center, 6300 Georgetown Pike, HSR-20, McLean, VA 22101-2296

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<jats:p> The empirical Bayes (EB) method addresses two problems of safety estimation: it increases the precision of estimates beyond what is possible when one is limited to the use of a 2- to 3-year accident history, and it corrects for the regression-to-mean bias. The increase in precision is important when the usual estimate is too imprecise to be useful. The elimination of the regression-to-mean bias is important whenever the accident history of the entity is in some way connected with the reason why its safety is estimated. The theory of the EB method is well developed. It is now used in the Interactive Highway Safety Design Model and will be used in the Comprehensive Highway Safety Improvement Model. The time has come for the EB method to be the standard and staple of professional practice. The study’s goal is to facilitate the transition from theory into practice. </jats:p>

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