McGrath Robert E, Meyer Gregory J
School of Psychology, Fairleigh Dickinson University, Teaneck, NJ 07666, USA.
Psychol Methods. 2006 Dec;11(4):386-401. doi: 10.1037/1082-989X.11.4.386.
The increased use of effect sizes in single studies and meta-analyses raises new questions about statistical inference. Choice of an effect-size index can have a substantial impact on the interpretation of findings. The authors demonstrate the issue by focusing on two popular effect-size measures, the correlation coefficient and the standardized mean difference (e.g., Cohen's d or Hedges's g), both of which can be used when one variable is dichotomous and the other is quantitative. Although the indices are often practically interchangeable, differences in sensitivity to the base rate or variance of the dichotomous variable can alter conclusions about the magnitude of an effect depending on which statistic is used. Because neither statistic is universally superior, researchers should explicitly consider the importance of base rates to formulate correct inferences and justify the selection of a primary effect-size statistic.
在单个研究和荟萃分析中效应量使用的增加引发了关于统计推断的新问题。效应量指标的选择会对研究结果的解释产生重大影响。作者通过关注两种常用的效应量度量方法来阐述这一问题，即相关系数和标准化均值差（如科恩d值或赫奇斯g值），当一个变量为二分变量而另一个为定量变量时，这两种方法均可使用。尽管这些指标在实际应用中常常可以互换，但对二分变量的基础率或方差的敏感性差异可能会根据所使用的统计量改变关于效应大小的结论。由于没有一种统计量是普遍优越的，研究人员应明确考虑基础率的重要性，以做出正确的推断并为主要效应量统计量的选择提供依据。
