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Power of the Cochran-Armitage trend test when exposure scores are based on empirical quantiles of exposure

机译：当暴露分数基于暴露的经验分位数时，Cochran-Armitage趋势检验的功效

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Epidemiologists often categorize exposures based on quantiles of exposure and use the Cochran-Armitage trend test based on such categories to detect associations between disease and exposure. Power calculations typically assume that the population quantiles are known, but in practice quantiles are often estimated from the sample data. We evaluated the power of the Cochran-Armitage trend test for cohort designs and for case-control designs in which sample quantiles of exposure in the cohort or in controls from a case-control study, respectively, are used to define the cut-points that separate exposure score categories. We give the asymptotic formulas for size and power for the Cochran-Armitage test based on empirical quantiles separately for cohort and case-control designs, together with efficient simulation methods to estimate size and power. Numerical results indicate that estimation of sample quantiles has only a slight effect on power for cohort studies with at least four categories or with more than 280 subjects. However, estimating quantiles can reduce power appreciably in smaller studies with fewer than four exposure categories. For case-control studies of rare diseases, the power loss is limited with more than 120 cases plus controls if the odds ratio comparting the highest exposure category to the lowest category is greater than 0.5. However, if that odd ratio is smaller than 0.5, only samples with more than 360 cases plus controls can guarantee a small loss of power, and increasing the number of exposure categories does not eliminate the loss of power.
机译：流行病学家经常根据暴露的分位数对暴露进行分类，并根据此类分类使用Cochran-Armitage趋势检验来检测疾病和暴露之间的关联。功效计算通常假设总体位数是已知的，但实际上，位数通常是根据样本数据估算的。我们评估了Cochran-Armitage趋势检验对于队列设计和案例对照设计的功效，在该案例中，分别使用队列中或案例对照研究中的样本暴露量来定义切点，单独的曝光分数类别。我们分别为队列和案例控制设计提供了基于经验分位数的Cochran-Armitage检验的大小和幂的渐近公式，以及有效的模拟方法来估计大小和幂。数值结果表明，对于至少四个类别或超过280个受试者的队列研究，样本分位数的估计仅对功效产生轻微影响。但是，在少于四个暴露类别的较小研究中，估计分位数可以显着降低功效。对于稀有疾病的病例对照研究，如果将最高暴露类别与最低暴露类别的比值比值大于0.5，则功率损失限制在120例以上且加上对照组。但是，如果该奇数比小于0.5，则只有超过360个案例加上对照的样本才能保证较小的功率损失，并且增加暴露类别的数量也不能消除功率损失。

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