Applying the compound Poisson process model to the reporting of injury-related mortality rates.

Scott R Kegler
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Abstract

Injury-related mortality rate estimates are often analyzed under the assumption that case counts follow a Poisson distribution. Certain types of injury incidents occasionally involve multiple fatalities, however, resulting in dependencies between cases that are not reflected in the simple Poisson model and which can affect even basic statistical analyses. This paper explores the compound Poisson process model as an alternative, emphasizing adjustments to some commonly used interval estimators for population-based rates and rate ratios. The adjusted estimators involve relatively simple closed-form computations, which in the absence of multiple-case incidents reduce to familiar estimators based on the simpler Poisson model. Summary data from the National Violent Death Reporting System are referenced in several examples demonstrating application of the proposed methodology.

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将复合泊松过程模型应用于与伤害相关的死亡率报告。
在分析与伤害相关的死亡率估计值时,通常假定病例数遵循泊松分布。然而,某些类型的伤害事故偶尔会涉及多人死亡,导致病例之间存在依赖关系,而这种依赖关系在简单的泊松模型中无法体现,甚至会影响基本的统计分析。本文探讨了作为替代方案的复合泊松过程模型,强调了对一些常用的基于人口的比率和比率比的区间估计值的调整。调整后的估计值涉及相对简单的闭式计算,在不存在多例事件的情况下,可简化为基于更简单的泊松模型的熟悉估计值。在应用建议方法的几个示例中,参考了国家暴力死亡报告系统的汇总数据。
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