Most previous research on motorcycle accident severity has focused on univariate relationships between severity and an explanatory variable of interest (e.g., helmet use). The potential ambiguity and bias that univariate analyses create in identifying the causality of severity has generated the need for multivariate analyses in which the effects of all factors that influence accident severity are considered. This paper attempts to address this need by presenting a multinomial logit formulation of motorcyclerider accident severity in single-vehicle collisions. Five levels of severity are considered:
1.
(a) property damage only,
2.
(b) possible injury,
3.
(c) evident injury,
4.
(d) disabling injury, and
5.
(e) fatality.