Helfenstein U
Biostatistical Center of the Medical Department, University of Zurich, Switzerland.
Accid Anal Prev. 1990 Feb;22(1):79-87. doi: 10.1016/0001-4575(90)90009-a.
In a statistical analysis of accident data before and after a speed limit reduction, the time of the countermeasure is, of course, well known. Our understanding of the accident process may, however, be increased if we assume in a thought experiment that this time is unknown. We ask if the data themselves can tell us something about such a possible time. By means of time series of traffic accidents in Zurich before and after a speed limit reduction, different exploratory methods are presented to identify the "unknown" time of this measure. For most of the investigated series, the most likely time was found to lie in the three months before the true introduction. A possible explanation of this result may be that the media already informed the public before the countermeasure was actually introduced. This finding leads to an improved parsimonious intervention model which distinguishes between a possible "preintervention effect" and the usual "intervention effect."
在对限速降低前后的事故数据进行统计分析时,当然,对策实施的时间是已知的。然而,如果我们在一个思想实验中假设这个时间是未知的,那么我们对事故过程的理解可能会得到增强。我们会问,数据本身能否告诉我们关于这个可能时间的一些信息。通过苏黎世限速降低前后交通事故的时间序列,提出了不同的探索性方法来确定这一对策的“未知”时间。对于大多数被调查的序列,发现最可能的时间是在实际实施前的三个月。这一结果的一个可能解释是,在对策实际实施之前,媒体就已经告知了公众。这一发现导致了一个改进的简约干预模型,该模型区分了可能的“干预前效应”和通常的“干预效应”。