Abstract
The presence of rare events in the accident data and transferability of error from one severity level to the other are just two of the issues in modelling accident severity. This paper explores the implications of different model structures and evaluation criteria using a common data set. Evaluation criteria are statistical fit of submodels, stability and validity of risk factors, overall model prediction, and case-specific model predictions. Model structures considered were the sequence of injury severity in the model structure, sequential versus nonsequential models, degree of aggregation, and case control approach. The study concluded that all the different models produce similar results. There is no indication of transferability of error between submodels in the sequential model. It was concluded that a disaggregate model is preferred to an aggregate model given the similarity of results. Key words: road accident severity, personal injury, logit, model choice.
Published Version
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