Scammacca Nancy, Roberts Greg, Stuebing Karla K
Nancy Scammacca, PhD, is a research associate at the Meadows Center for Preventing Educational Risk in the College of Education at the University of Texas at Austin, 1 University Station D4900, Austin, TX 78712.
Greg Roberts, PhD, is the director of the Vaughn Gross Center for Reading and Language Arts and the associate director of the Meadows Center for Preventing Educational Risk at the University of Texas at Austin.
Rev Educ Res. 2014 Sep 1;84(3):328-364. doi: 10.3102/0034654313500826.
Previous research has shown that treating dependent effect sizes as independent inflates the variance of the mean effect size and introduces bias by giving studies with more effect sizes more weight in the meta-analysis. This article summarizes the different approaches to handling dependence that have been advocated by methodologists, some of which are more feasible to implement with education research studies than others. A case study using effect sizes from a recent meta-analysis of reading interventions is presented to compare the results obtained from different approaches to dealing with dependence. Overall, mean effect sizes and variance estimates were found to be similar, but estimates of indexes of heterogeneity varied. Meta-analysts are advised to explore the effect of the method of handling dependence on the heterogeneity estimates before conducting moderator analyses and to choose the approach to dependence that is best suited to their research question and their data set.
先前的研究表明，将相关效应量视为独立的会夸大平均效应量的方差，并在元分析中给予具有更多效应量的研究更大权重，从而引入偏差。本文总结了方法学家所倡导的处理相关性的不同方法，其中一些方法在教育研究中比其他方法更易于实施。本文呈现了一个案例研究，该研究使用了近期一项阅读干预元分析中的效应量，以比较从不同处理相关性方法中获得的结果。总体而言，发现平均效应量和方差估计值相似，但异质性指标的估计值有所不同。建议元分析师在进行调节分析之前，探究处理相关性的方法对异质性估计的影响，并选择最适合其研究问题和数据集的相关性处理方法。
