In accident injury-severity analysis, an inherent limitation of the traditional ordered probit approach arises from the a priori consideration of a homogeneous source for the accidents that result in a no-injury (or zero-injury) outcome. Conceptually, no-injury accidents may be subject to the effect of two underlying injury-severity states, which are more likely to be observed in accident datasets with excessive amounts of no-injury accident observations. To account for this possibility along with the possibility of heterogeneity stemming from the fixed nature of the ordered probability thresholds, a zero-inflated hierarchical ordered probit approach with correlated disturbances is employed, for the first time – to the authors’ knowledge – in accident research. The latter consists of a binary probit and an ordered probit component that are simultaneously modeled in order to identify the influential factors for each underlying injury-severity state. At the same time, the model formulation accounts for possible correlation between the disturbance terms of the two model components, and allows for the ordered thresholds to vary as a function of threshold-specific explanatory variables. Using injury-severity data from single-vehicle accidents that occurred in the State of Washington, from 2011 to 2013, the implementation potential of the proposed approach is demonstrated. The comparative assessment between the zero-inflated hierarchical ordered probit approach with correlated disturbances and its lower-order counterparts highlights the potential of the proposed approach to account for the effect of underlying states on injury-severity outcome probabilities and to explain more with the same amount of information.

在事故伤害严重性分析中，传统的有序概率模型方法的固有局限性在于先验考虑导致无伤害（或零伤害）结果的事故的同类来源。从概念上讲，无伤害事故可能会受到两个潜在伤害严重性状态的影响，这在有大量无伤害事故观察值的事故数据集中更可能被观察到。为了解决这种可能性以及由于有序概率阈值的固定性质而导致的异质性的可能性，在事故研究中，据作者所知，这是首次采用零膨胀的具有相关干扰的分层有序概率模型。 。后者由一个二进制概率和一个有序概率组成，它们被同时建模以识别每个潜在的伤害严重性状态的影响因素。同时，模型公式考虑了两个模型组件的干扰项之间可能的相关性，并允许有序阈值根据特定于阈值的解释变量而变化。使用2011年至2013年在华盛顿州发生的单车事故的伤害严重性数据，证明了该方法的实施潜力。具有相关干扰的零膨胀层次有序概率方法与低阶对应方法之间的比较评估突出了该方法在考虑潜在状态对伤害严重性结果概率的影响并用相同数量进行解释时的潜力信息。