Abstract:
Statistical modelling techniques are widely used in accident studies. It is a well-known fact that frequentist
statistical approach includes hypothesis testing, correlations, and probabilistic inferences. Bayesian networks,
which belong to the set of advanced AI techniques, perform advanced calculations related to diagnostics,
prediction and causal inference. The aim of the current work is to present a comparison of Bayesian and
Regression approaches for safety analysis. For this, both advantages and disadvantages of two modelling
approaches were studied. The results indicated that the precision of Bayesian network was higher than that of
the ordinal regression model. However, regression analysis can also provide understanding of the information
hidden in data. The two approaches may suggest different significant explanatory factors/causes, and this
always should be taken into consideration. The obtained outcomes from this analysis will contribute to the
existing literature on safety science and accident analysis.