A primer on the understanding, use, and calculation of confidence intervals that are based on central and noncentral distributions
A primer on the understanding, use, and calculation of confidence intervals that are based on central and noncentral distributions
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DOI：
10.1177/0013164401614002
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发表时间：
2001-08-01
影响因子：
2.7
通讯作者：
Finch, S
中科院分区：
文献类型：
--
作者：
Cumming, G;Finch, S
社会和行为科学统计实践的改革需要更广泛地使用置信区间（CI）、效应量测量和荟萃分析。作者讨论了促进使用CI的四个原因：它们（a）易于解释，（B）与熟悉的统计显著性检验有关，（c）可以鼓励元分析思维，（d）提供有关精度的信息。作者讨论了一个基本的标准化效应量测量，科恩的三角洲（也称为科恩的d），并将这些与熟悉的原始评分均值的CI的计算。Delta的CI需要使用非中心t分布，作者也将其应用于统计功效和标准化效应量的简单荟萃分析。他们提供了在Microsoft Excel下运行的ESCI图形软件来说明讨论。更广泛地使用三角洲和其他效应量指标的CI应有助于促进社会科学统计实践的高度可取的改革。
Reform of statistical practice in the social and behavioral sciences requires wider use of confidence intervals (CIs), effect size measures, and meta-analysis. The authors discuss four reasons for promoting use of CIs: They (a) are readily interpretable, (b) are linked to familiar statistical significance tests, (c) can encourage meta-analytic thinking, and (d) give information about precision. The authors discuss calculation of Cls for a basic standardized effect size measure, Cohen's delta (also known as Cohen's d), and contrast these with the familiar CIs for original score means. CIs for delta require use of noncentral t distributions, which the authors apply also to statistical power and simple meta-analysis of standardized effect sizes. They provide the ESCI graphical software, which runs under Microsoft Excel, to illustrate the discussion. Wider use of CIs for delta and other effect size measures should help promote highly desirable reform of statistical practice in the social sciences.