Xing Guan, Ku Hung-Chih, Xing Chao
Bristol-Myers Squibb Company, 311 Pennington-Rocky Hill Road, Pennington, NJ, USA.
Ann Hum Genet. 2013 Jul;77(4):333-5. doi: 10.1111/ahg.12022. Epub 2013 Mar 14.
In a recent paper in this journal, the use of variance-stabilising transformation techniques was proposed to overcome the problem of inadequacy in normality approximation when testing association for a low-frequency variant in a case-control study. It was shown that tests based on the variance-stabilising transformations are more powerful than Fisher's exact test while controlling for type I error rate. Earlier in the journal, another study had shown that the likelihood ratio test (LRT) is superior to Fisher's exact test, Wald's test, and Pearson's χ(2) test in testing association for low-frequency variants. Thus, it is of interest to make a direct comparison between the LRT and the tests based on the variance-stabilising transformations. In this commentary, we show that the LRT and the variance-stabilising transformation-based tests have comparable power greater than Fisher's exact test, Wald's test, and Pearson's χ(2) test.
在本期刊最近发表的一篇论文中,有人提出使用方差稳定变换技术,以克服在病例对照研究中对低频变异进行关联性检验时正态近似不足的问题。结果表明,在控制I型错误率的同时,基于方差稳定变换的检验比费舍尔精确检验更具功效。在本期刊早期,另一项研究表明,在对低频变异进行关联性检验时,似然比检验(LRT)优于费舍尔精确检验、Wald检验和Pearson卡方检验。因此,直接比较LRT和基于方差稳定变换的检验很有意义。在这篇评论中,我们表明LRT和基于方差稳定变换的检验具有可比的功效,且大于费舍尔精确检验、Wald检验和Pearson卡方检验。