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Odds ratio for a single 2 × 2 table with correlated binomials for two margins

机译:一张带有相关二项式的两个2边距的单个2×2表的几率

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While analyzing 2 × 2 contingency tables, the log odds ratio for measuring the strength of association is often approximated by a normal distribution with some variance. We show that the expression of that variance needs to be modified in the presence of correlation between two binomial distributions of the contingency table. In the present paper, we derive a correlation-adjusted variance of the limiting normal distribution of log odds ratio. We also propose a correlation adjusted test based on the standard odds ratio for analyzing matched-pair studies and any other study settings that induce correlated binary outcomes. We demonstrate that our proposed test outperforms the classical McNemar's test. Simulation studies show the gains in power are especially manifest when sample size is small and strong correlation is present. Two examples of real data sets are used to demonstrate that the proposed method may lead to conclusions significantly different from those reached using McNemar's test.
机译:在分析2×2列联表时,用于衡量关联强度的对数比值比通常通过正态分布进行近似估计,并具有一定的方差。我们表明,在列联表的两个二项式分布之间存在相关性的情况下,需要修改该方差的表达式。在本文中,我们推导了对数优势比的极限正态分布的相关调整方差。我们还建议根据标准比值比进行相关调整的测试,以分析匹配对研究和诱发相关二元结果的任何其他研究设置。我们证明了我们提出的测试优于经典的McNemar测试。仿真研究表明,当样本量较小且存在强相关性时,功效的提高尤其明显。使用实际数据集的两个示例来证明所提出的方法可能得出与使用McNemar检验得出的结论明显不同的结论。

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