Generalized eta and omega squared statistics: Measures of effect size for some common research designs
Generalized eta and omega squared statistics: Measures of effect size for some common research designs
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DOI：
10.1037/1082-989x.8.4.434
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发表时间：
2003-12-01
影响因子：
7
通讯作者：
Algina, J
中科院分区：
文献类型：
--
作者：
Olejnik, S;Algina, J
几个著名的教育和心理学期刊的编辑政策要求研究人员报告一些测量效果的大小沿着测试的统计意义。在方差分析上下文中，可以通过使用eta平方或omega平方统计量来满足此要求。目前用于计算这些效应度量的程序通常不考虑研究的设计特征对这些统计量的大小的影响。由于研究设计特征对解释方差的估计比例有很大影响，使用偏eta或omega平方可能会产生误导。本文提供了计算广义η和Ω平方统计量的公式，这些公式提供了在各种研究设计中具有可比性的效应量估计值。
The editorial policies of several prominent educational and psychological journals require that researchers report some measure of effect size along with tests for statistical significance. In analysis of variance contexts, this requirement might be met by using eta squared or omega squared statistics. Current procedures for computing these measures of effect often do not consider the effect that design features of the study have on the size of these statistics. Because research-design features can have a large effect on the estimated proportion of explained variance, the use of partial eta or omega squared can be misleading. The present article provides formulas for computing generalized eta and omega squared statistics, which provide estimates of effect size that are comparable across a variety of research designs.