Recommended effect size statistics for repeated measures designs
Recommended effect size statistics for repeated measures designs
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DOI：
10.3758/bf03192707
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发表时间：
2005-08-01
影响因子：
5.4
通讯作者：
Bakeman, R
中科院分区：
文献类型：
--
作者：
Bakeman, R
越来越多的研究者被要求提供和讨论效应量统计数据，如果他们更清楚地了解需要什么，他们可能会更经常地遵守。当研究人员希望报告从方差分析得出的效应量时，包括重复测量，过去的建议是有问题的。直到最近才提出了一个普遍有用的效应量统计量：广义eta平方（eta（2）（G）; Olejnik & Algina，2003）。在这里，我们介绍了这种方法，解释了eta（2）（G）更喜欢eta平方和偏eta平方，因为它提供了跨受试者间和受试者内设计的可比性，表明它可以很容易地从标准统计软件包提供的信息计算，并建议研究者在适当的时候在他们的研究报告中定期提供它。
Investigators, who are increasingly implored to present and discuss effect size statistics, might comply more often if they understood more clearly what is required. When investigators wish to report effect sizes derived from analyses of variance that include repeated measures, past advice has been problematic. Only recently has a generally useful effect size statistic been proposed for such designs: generalized eta squared (eta(2)(G); Olejnik & Algina, 2003). Here, we present this method, explain that eta(2)(G) preferred to eta squared and partial eta squared because it provides comparability across between-subjects and within-subjects designs, show that it can easily be computed from information provided by standard statistical packages, and recommend that investigators provide it routinely in their research reports when appropriate.