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.
Statistics Statistical inference Mean plots Confidence intervals Within-subject designs
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We would like to thank Bradley Harding, Christophe Tremblay, Thom Baguley, and an anonymous reviewer for their comments on an earlier version of this text.
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