Error bars in within-subject designs: a comment on Baguley (2012)

被引:0
|
作者
Denis Cousineau
Fearghal O’Brien
机构
[1] Université d’Ottawa,École de psychologie
[2] Aras an Phiarsigh,School of Psychology
[3] Trinity College,undefined
来源
Behavior Research Methods | 2014年 / 46卷
关键词
Statistics; Statistical inference; Mean plots; Confidence intervals; Within-subject designs;
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学科分类号
摘要
The problem of calculating error bars in within-subject designs has proven to be a difficult problem and has received much attention in recent years. Baguley (Behavior Research Methods, 44, 158–175, 2012) recommended what he called the Cousineau–Morey method. This method requires two steps: first, centering the data set in a certain way to remove between-subject differences and, second, integrating a correction factor to debias the standard errors obtained from the normalized data set. However, within some statistical packages, it can be difficult to integrate this correction factor. Baguley (2012) proposed a solution that works well in most statistical packages in which the alpha level is altered to incorporate the correction factor. However, with this solution, it is possible to plot confidence intervals, but not standard errors. Here, we propose a second solution that can return confidence intervals or standard error bars in a mean plot.
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页码:1149 / 1151
页数:2
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