Department of Mathematics, RLM 10.144, University of Texas at Austin, 2515 Speedway, Austin, TX 78712, USA.
Biostatistics. 2014 Jan;15(1):74-86. doi: 10.1093/biostatistics/kxt028. Epub 2013 Aug 22.
We provide evidence that, in certain circumstances, a root-mean-square test of goodness of fit can be significantly more powerful than state-of-the-art tests in detecting deviations from Hardy-Weinberg equilibrium. Unlike Pearson's $\chi ^2$ test, the log-likelihood-ratio test, and Fisher's exact test, which are sensitive to relative discrepancies between genotypic frequencies, the root-mean-square test is sensitive to absolute discrepancies. This can increase statistical power, as we demonstrate using benchmark data sets and simulations, and through asymptotic analysis.
我们提供的证据表明，在某些情况下，拟合优度的均方根检验比检测哈迪-温伯格平衡偏离的最先进检验具有显著更高的功效。与皮尔逊卡方检验、对数似然比检验和 Fisher 确切检验不同，后者对基因型频率之间的相对差异敏感，均方根检验对绝对差异敏感。我们使用基准数据集和模拟以及通过渐近分析证明了这一点，这可以提高统计功效。
