文章基本信息

标题：Constructing Confidence Intervals for Effect Sizes in ANOVA Designs
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作者：Chen, Li-Ting ; Peng, Chao-Ying Joanne
期刊名称：Journal of Modern Applied Statistical Methods
出版年度：2013
卷号：12
期号：2
页码：5
出版社：Wayne State University
摘要：A confidence interval for effect sizes provides a range of plausible population effect sizes (ES) that are consistent with data. This article defines an ES as a standardized linear contrast of means. The noncentral method, Bonett’s method, and the bias-corrected and accelerated bootstrap method are illustrated for constructing the confidence interval for such an effect size. Results obtained from the three methods are discussed and interpretations of results are offered.
关键词：Confidence interval; linear contrast; effect size; bootstrap; noncentral