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Statistical adjustment for misclassification of seat belt and alcohol use in the analysis of motor vehicle accident data

机译:对汽车事故数据分析中的安全带和酒精使用分类错误的统计调整

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摘要

The use of seat belts and alcohol is often misreported in police motor vehicle accident reports for a number of reasons. To avoid penalties, occupants often over report seat belt use and under report alcohol use. Police officers sometimes fail to account for evidence such as presence of belt burn, condition of belts, odor of alcohol, crash patterns, etc. Biased conclusions result when using misclassified accident data to estimate the effectiveness of seat belts in preventing injuries and reducing medical costs. We investigated the effects of misclassification of seat belt and alcohol use on the odds ratio of injury as well as medical costs. A statistical method and a SAS program were developed to adjust odds ratios of injury and medical cost estimates to account for misclassification of seat belts and alcohol use. The method allowed for incorporation of variables that could affect misclassification of seat belt and alcohol use. We conducted a Monte Carlo simulation and found that when there were large differences between the misclassification rates for major and minor injury, the unadjusted odds ratio could have up to a 90% bias while our adjusted odds ratio was effectively unbiased. To illustrate the method, we estimated the misclassification rates of seat belt and alcohol use by comparing merged police and hospital reports from Nebraska motor vehicle accident data sets (1996-1997) and then evaluated the bias of the odds ratio of injury and medical costs estimates due to misclassification. Our results showed that the bias of the odds ratio of injury and medical costs due to misclassification of seat belts and alcohol use depended both on the amount of misclassification and the reported frequencies. Misclassification about seat belt and alcohol use only slightly biased the unadjusted odds ratio estimates and mean hospital charge, while misclassification resulted in approximately a 69% underestimate of the total medical costs savings due to seatbelts. However, due to the small size of the merged Nebraska police and hospital data set used to estimate misclassification rates, these results are likely somewhat imprecise.
机译:由于多种原因,在警察机动车辆事故报告中经常错误地使用安全带和酒精。为了避免罚款,乘员经常报告安全带使用过高而酒精饮料使用过少。警务人员有时无法解释证据,例如是否存在安全带烧伤,安全带状况,酒精气味,碰撞模式等。使用错误分类的事故数据来估计安全带在预防伤害和降低医疗费用方面的有效性时,会得出有偏见的结论。 。我们调查了安全带和酒精使用分类错误对受伤几率和医疗费用的影响。开发了一种统计方法和一个SAS程序来调整伤害和医疗费用估算的比值比,以解决安全带和酒精使用的错误分类。该方法考虑了可能影响安全带分类错误和酒精使用的变量。我们进行了蒙特卡洛模拟,发现当重伤和轻伤的错误分类率之间存在较大差异时,未经调整的优势比可能会有高达90%的偏差,而我们的经过调整的优势比实际上是无偏的。为了说明这种方法,我们通过比较内布拉斯加州机动车事故数据集(1996-1997年)的合并警察和医院报告,估算了安全带和酒精使用的误分类率,然后评估了伤害几率比和医疗费用估算值的偏差。由于分类错误。我们的结果表明,由于安全带分类错误和饮酒所致伤害和医疗费用比值比的偏差取决于分类错误的数量和报告的频率。关于安全带和酒精使用的错误分类仅使未调整的优势比估算值和平均住院费用略有偏差,而错误分类导致由于安全带而导致的总医疗费用节省被低估了约69%。但是,由于用于估计错误分类率的内布拉斯加警察和医院数据集的合并量很小,因此这些结果可能有些不准确。

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