This paper examines the predictive validity of empirical Bayes (EB) estimates of road safety. All versions of EB-estimates are compared to the traditional, naive assumption of treating the recorded number of accidents as an unbiased estimate of the expected number of accidents. To test the predictive performance of EB-estimates, data for two periods was used. EB-estimates based on data for the first period were treated as predictions of the number of accidents in the second period for road sections that had 0, 1, 2, etc., accidents in the first period, the idea being that the more accurate the prediction, the more accurate the result of a before-and-after study. All versions of EB-estimates were found to give considerably more correct predictions of the number of accidents in the second period than relying on the count of accidents in the first period as a prediction of the count in the second period. Smaller prediction errors were associated withpredictions based on accident prediction models than predictions not based on such models. (A) Reprinted with permission from Elsevier.
Samenvatting