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文章基本信息

  • 标题:Constructing Confidence Intervals for Effect Sizes in ANOVA Designs
  • 本地全文:下载
  • 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
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