Yoder Paul J, Blackford Jennifer Urbano, Waller Niels G, Kim Geunyoung
Kennedy Center, Vanderbilt University, Peabody Box 328, Nashville, TN 37203, USA.
J Clin Exp Neuropsychol. 2004 May;26(3):320-31. doi: 10.1080/13803390490510040.
This study examined the relative family-wise error (FWE) rate and statistical power of multivariate permutation tests (MPTs), Bonferroni-adjusted alpha, and uncorrected-alpha tests of significance for bivariate associations. Although there are many previous applications of MPTs, this is the first to apply it to testing bivariate associations. Electrocortical studies were selected as an example class because the sample sizes that are typical of electrocortical studies published in 2001 and 2002 are small and their multiple significance tests are typically nonindependent. Because Bonferroni adjustments assume independent predictors, we expected that MPTs would be more powerful than the Bonferroni adjustment. Results support the following conclusions: (a) failure to control for multiple significance testing results in unacceptable FWE rates, (b) the FWE rate for the MPTs approximated the alpha set for the analyses, and (c) the statistical power advantage that MPTs provide over Bonferroni adjustments is important when using small sample sizes such as those that are typical of recent electrocortical studies.
本研究考察了多变量置换检验（MPT）、Bonferroni校正的α水平以及双变量关联显著性的未校正α检验的相对家族性错误率（FWE）和统计功效。尽管此前已有许多MPT的应用，但这是首次将其应用于双变量关联检验。选择脑电研究作为示例类别，是因为2001年和2002年发表的脑电研究典型样本量较小，且其多重显著性检验通常是非独立的。由于Bonferroni校正假定预测变量是独立的，我们预期MPT比Bonferroni校正更具功效。结果支持以下结论：（a）未能控制多重显著性检验会导致不可接受的FWE率；（b）MPT的FWE率接近为分析设定的α水平；（c）当使用小样本量（如近期脑电研究的典型样本量）时，MPT相对于Bonferroni校正所具有的统计功效优势很重要。
