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Effect sizes, confidence intervals, and confidence intervals for effect sizes

机译:效果大小,置信区间和效果大小的置信区间

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摘要

The present article provides a primer on (a) effect sizes, (b) confidence intervals, and (c) confidence intervals for effect sizes. Additionally, various admonitions for reformed statistical practice are presented. For example, a very important implication of the realization that there are dozens of effect size statistics is that authors must explicitly tell readers what effect sizes they are reporting. With respect to confidence intervals, when interpreting a 95% interval, we should never say that we are 95% confident that our interval captures the estimated population parameter. It is explained that effect sizes should be reported even for statistically nonsignificant effects. And, most importantly of all, it is emphasized that effect sizes should not be interpreted using Cohen's benchmarks. Instead, we ought to interpret our effects in direct and explicit comparison against the effects in the related prior literature. (c) 2007 Wiley Periodicals, Inc.
机译:本文提供了关于(a)效果大小,(b)置信区间和(c)效果大小的置信区间的入门。此外,还提出了各种改革统计实践的建议。例如,意识到存在数十种效果大小统计数据的一个非常重要的含义是,作者必须明确告知读者他们所报告的效果大小。关于置信区间,在解释95%区间时,我们永远不要说我们有95%的信心说我们的区间捕获了估计的总体参数。据解释,即使是统计学上不显着的影响,也应报告影响大小。而且,最重要的是,强调不应使用Cohen的基准来解释效果大小。相反,我们应该通过与相关现有文献中的影响进行直接和显式比较来解释我们的影响。 (c)2007年Wiley Periodicals,Inc.

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