01478716

Component

Regression to the mean (RTM) has been recognized as a phenomenon that influences road safety evaluations and should be accounted for. However, some doubts have risen about the necessity to implement rather sophisticated techniques such as the empirical Bayes method to correct for regression to the mean whereas the use of a sufficient long before-period could reach the same objective. Present study examines the existence and the magnitude of the regression to the mean effect in crash data from 169 intersections for the injury crashes and 143 for the more severe crashes in Flanders-Belgium for whom regression to the mean was likely to occur as they were selected based on their crash history. The presence of a RTM-effect was investigated by comparing the crash numbers of this period with the crash numbers in the next three years, during which no traffic safety measure was applied. Two comparison groups were used. The results demonstrate the existence of a substantial regression to the mean effect in the investigated sample of intersections. The magnitude of the regression to the mean effect is estimated to be almost 9% for injury crashes and 37% for the most severe crashes. From this can be concluded the correction for regression to the mean in evaluation studies is highly recommended in cases when locations are selected based on their crash history. This can be applied through the Empirical Bayes method.

This paper was sponsored by TRB committee ANB20 Safety Data, Analysis and Evaluation.

01470560

13-3772

English

12p

2013

Transportation Research Board 92nd Annual Meeting

Digital/other

References; Tables

Bayes' theorem; Before and after studies; Crash rates; Crashes; Mean (Statistics); Regression analysis; Traffic crashes; Traffic safety

Flanders (Belgium)

Data and Information Technology; Highways; Safety and Human Factors; I81: Accident Statistics

Transportation Research Board Annual Meeting 2013 Paper #13-3772

TRIS, TRB, ATRI

Feb 5 2013 12:44PM