Lei Li

TL;DR: It is found that driver behaviors of alcohol or drug use and lack of seat belt use greatly increase the odds of more severe crashes and injuries.

TL;DR: This paper uses a logistic regression model that allows for misclassification errors in outcome variable to examine predictors of safety belt use among crash-involved drivers and front seat passengers and shows significant associations between occupant characteristics, driving circumstances, and safety belts use.

TL;DR: Using log-linear modeling techniques, the probability of fault among collision-involved drivers in Hawaii is related to three categorical variables: age, sex, and vehicle type as discussed by the authors.

TL;DR: It can be concluded that bicyclists tend to be young, male, and, not surprisingly, more likely to be seriously injured than motorists in bicycle-motor-vehicle collisions.

TL;DR: In this paper, the authors developed a statistical description of patterns of motor-vehicle crash types among drivers of different age and sex in order to identify underlying differences in behavior and ability.