Calculating and graphing within-subject confidence intervals for ANOVA
Calculating and graphing within-subject confidence intervals for ANOVA
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DOI：
10.3758/s13428-011-0123-7
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发表时间：
2012-03-01
影响因子：
5.4
通讯作者：
Baguley, Thom
中科院分区：
文献类型：
--
作者：
Baguley, Thom
心理学和统计学文献包含了几个关于计算和绘制受试者内（重复测量）方差分析设计置信区间（ci）的建议。关键的区别在于支持均值模式推断的区间（特别是均值对之间的差异）和支持单个均值推断的区间。在本报告中，我们认为前者的ci最好是通过调整Cousineau（《心理学定量方法教程》，2005年第1期，42-45页）和Morey（《心理学定量方法教程》，2008年第4期，61-64页）提出的区间来实现的，这样，个体均值的非重叠ci对应于它们的差值的置信度不包括零。后者的ci可以通过拟合多层模型来完成。在对两种类型的推理都感兴趣的情况下，建议使用两层CI。这种区间估计和图（以及一些常见的替代方案）的免费、开源、跨平台软件以R函数的形式提供，用于受试者内的单向和双向混合ANOVA设计。这些功能为在主题ci内计算和显示难题提供了易于使用的解决方案。
The psychological and statistical literature contains several proposals for calculating and plotting confidence intervals (CIs) for within-subjects (repeated measures) ANOVA designs. A key distinction is between intervals supporting inference about patterns of means (and differences between pairs of means, in particular) and those supporting inferences about individual means. In this report, it is argued that CIs for the former are best accomplished by adapting intervals proposed by Cousineau (Tutorials in Quantitative Methods for Psychology, 1, 42-45, 2005) and Morey (Tutorials in Quantitative Methods for Psychology, 4, 61-64, 2008) so that nonoverlapping CIs for individual means correspond to a confidence for their difference that does not include zero. CIs for the latter can be accomplished by fitting a multilevel model. In situations in which both types of inference are of interest, the use of a two-tiered CI is recommended. Free, open-source, cross-platform software for such interval estimates and plots (and for some common alternatives) is provided in the form of R functions for one-way within-subjects and two-way mixed ANOVA designs. These functions provide an easy-to-use solution to the difficult problem of calculating and displaying within-subjects CIs.