A BIVARIATE NEGATIVE BINOMIAL MODEL TO EXPLAIN TRAFFIC ACCIDENT MIGRATION
A BIVARIATE NEGATIVE BINOMIAL MODEL TO EXPLAIN TRAFFIC ACCIDENT MIGRATION
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DOI：
10.1016/0001-4575(90)90043-k
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发表时间：
1990-10-01
影响因子：
5.9
通讯作者：
MAHER, MJ
中科院分区：
文献类型：
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作者：
MAHER, MJ
在研究交通意外黑点补救措施的成效时，“回归平均数”的现象已广为人知。发生的情况是，用于选择治疗部位的标准在有效性估计中产生了偏倚：即使治疗完全无效，后频率的条件期望值也小于真实均值。据报道，在一些以前的研究中，已经观察到事故“迁移”。这是一种现象，即在未经处理但邻近已处理场地的场地，事故率明显上升。如果这是一个真正的影响，它将对补救治疗的评估产生严重影响。本文的目的是解释这种迁移效应在纯粹的概率方面，没有诉诸物理迁移的概念。所用的模型是一个新的双变量负二项分布，将空间之间的相关性，真正的平均现场事故率。与回归平均值效应一样，迁移效应也可以用选择过程中隐含的条件反射来解释。
The phenomenon of “regression to the mean” is now widely known in the study of the effectiveness of remedial treatment of traffic accident blackspots. What happens is that the criterion used for selection of sites at which treatment is to be applied gives rise to bias in the estimate of the effectiveness: the conditional expectation of the after frequency is less than the true mean, even if the treatment is totally ineffective. It has been reported in some previous studies that accident “migration” has been observed. This is the phenomenon whereby the accident rate apparently rises at sites that are untreated but that are neighbours to treated sites. If this were a genuine effect, it would have serious implications for the assessment of remedial treatments. This paper aims to explain this migration effect in purely probabilistic terms, without recourse to the concept of physical migration. The model used is a new bivariate negative binomial distribution, incorporating spatial correlation between the true mean site accident rates. As with the regression to mean effect, the migration effect can then be explained in terms of the conditioning implicit in the selection process.