Abstract
Data from the National Accident Sampling System (NASS) are used to construct linear regression models with prior recorded accidents as the dependent variable. The results of univariate and multivariate analysis demonstrate that heavy truck drivers form a discreet subset of all accident-involved drivers, whose accident history is more reliably predicted by a more parsimonious model as compared to drivers of other vehicles types.