This note aims at providing a Bayesian methodological basis for routine before-after accident studies, often applied to a single road site, and in conditions of limited resources in terms of time and expertise. A low-informative Bayesian method is proposed for before-after accident studies using a comparison site or group of sites. As compared to conventional statistics, the Bayesian approach is less subject to misuse and misinterpretation by practitioners. The low-informative framework seems appropriate in situations of limited expertise. The proposed approach gives the possibility of correcting for regression to the mean. Examples illustrate the application of this method. It is shown that a relatively simple method, based on the Jeffreys’s rule prior considered as a 'reasonable standard', can be implemented without major difficulties. Posterior distributions are proper. The numerical calculation of posterior probabilities can be done without using Monte-Carlo simulations nor specialised software tools. (Author/publisher
Abstract