Dept. of Civil Engineering, University of British Columbia, Vancouver, BC, Canada V6T 1Z4.
Accid Anal Prev. 2009 Sep;41(5):1118-23. doi: 10.1016/j.aap.2009.06.025. Epub 2009 Jul 15.
Recent research advocates the use of count models with random parameters as an alternative method for analyzing accident frequencies. In this paper a dataset composed of urban arterials in Vancouver, British Columbia, is considered where the 392 segments were clustered into 58 corridors. The main objective is to assess the corridor effects with alternate specifications. The proposed models were estimated in a Full Bayes context via Markov Chain Monte Carlo (MCMC) simulation and were compared in terms of their goodness of fit and inference. A variety of covariates were found to significantly influence accident frequencies. However, these covariates resulted in random parameters and thereby their effects on accident frequency were found to vary significantly across corridors. Further, a Poisson-lognormal (PLN) model with random parameters for each corridor provided the best fit. Apart from the improvement in goodness of fit, such an approach is useful in gaining new insights into how accident frequencies are influenced by the covariates, and in accounting for heterogeneity due to unobserved road geometrics, traffic characteristics, environmental factors and driver behavior. The inclusion of corridor effects in the mean function could also explain enough variation that some of the model covariates would be rendered non-significant and thereby affecting model inference.
最近的研究提倡使用具有随机参数的计数模型作为分析事故频率的替代方法。本文考虑了一个由不列颠哥伦比亚省温哥华市的城市干道组成的数据集，其中 392 个路段被聚类为 58 个走廊。主要目标是评估替代规范的走廊效应。所提出的模型通过马尔可夫链蒙特卡罗 (MCMC) 模拟在全贝叶斯上下文中进行了估计，并在拟合优度和推断方面进行了比较。发现多种协变量会显著影响事故频率。然而，这些协变量导致了随机参数，从而发现它们对事故频率的影响在各个走廊之间有很大差异。此外，每个走廊的具有随机参数的泊松-对数正态 (PLN) 模型提供了最佳拟合。除了拟合优度的提高之外，这种方法还有助于深入了解协变量如何影响事故频率，并考虑由于未观察到的道路几何形状、交通特征、环境因素和驾驶员行为而导致的异质性。在均值函数中包含走廊效应还可以解释足够的变化，从而使某些模型协变量变得不显著，从而影响模型推断。
