Department of Integrative Biology, University of South Florida, 4202 East Fowler Avenue, Tampa, Florida 33620, USA.
Ecology. 2011 Nov;92(11):2049-55. doi: 10.1890/11-0423.1.
A common effect size metric used to quantify the outcome of experiments for ecological meta-analysis is the response ratio (RR): the log proportional change in the means of a treatment and control group. Estimates of the variance of RR are also important for meta-analysis because they serve as weights when effect sizes are averaged and compared. The variance of an effect size is typically a function of sampling error; however, it can also be influenced by study design. Here, I derive new variances and covariances for RR for several often-encountered experimental designs: when the treatment and control means are correlated; when multiple treatments have a common control; when means are based on repeated measures; and when the study has a correlated factorial design, or is multivariate. These developments are useful for improving the quality of data extracted from studies for meta-analysis and help address some of the common challenges meta-analysts face when quantifying a diversity of experimental designs with the response ratio.
用于量化生态元分析实验结果的常用效应量指标是反应比 (RR)：处理组和对照组均值对数比例变化。RR 的方差估计对于元分析也很重要，因为它们在平均和比较效应量时充当权重。效应量的方差通常是抽样误差的函数；然而，它也可能受到研究设计的影响。在这里，我为几种常见的实验设计推导出 RR 的新方差和协方差：当处理组和对照组均值相关时；当多个处理组有一个共同的对照组时；当均值基于重复测量时；当研究具有相关的析因设计或多元设计时。这些发展有助于提高从元分析中提取研究数据的质量，并有助于解决元分析人员在使用反应比量化各种实验设计时面临的一些常见挑战。
