Fridstrøm L, Ingebrigtsen S
Institute of Transport Economics, Oslo, Norway.
Accid Anal Prev. 1991 Oct;23(5):363-78. doi: 10.1016/0001-4575(91)90057-c.
The determinants of personal injury road accidents and their severity are studied by means of generalized Poisson regression models estimated on the basis of combined cross-section/time-series data. Monthly data have been assembled for 18 Norwegian counties (every county but one), covering the period from January 1974 until December 1986. A rather wide range of potential explanatory factors are taken into account, including road use (exposure), weather, daylight, traffic density, road investment and maintenance expenditure, accident reporting routines, vehicle inspection, law enforcement, seat belt usage, proportion of inexperienced drivers, and alcohol sales. Separate probability models are estimated for the number of personal injury accidents, fatal accidents, injury victims, death victims, car occupants injured, and bicyclists and pedestrians injured. The fraction of personal injury accidents that are fatal is interpreted as an average severity measure and studied by means of a binomial logit model.
利用基于混合横截面/时间序列数据估计的广义泊松回归模型，对人身伤害道路事故的决定因素及其严重程度进行了研究。收集了18个挪威郡（除一个郡外的每个郡）的月度数据，涵盖1974年1月至1986年12月期间。考虑了相当广泛的潜在解释因素，包括道路使用（暴露）、天气、日照、交通密度、道路投资和维护支出、事故报告程序、车辆检查、执法、安全带使用、无经验驾驶员比例以及酒精销售情况。针对人身伤害事故数量、致命事故、受伤受害者、死亡受害者、车内乘客受伤情况以及骑自行车者和行人受伤情况分别估计了概率模型。将致命的人身伤害事故比例解释为平均严重程度度量，并通过二项式logit模型进行研究。
