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

• Published in: Behavior research methods Vol. 46; no. 4; pp. 1149 - 1151
• Main Authors: Cousineau, Denis, O’Brien, Fearghal
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.12.2014; Springer Nature B.V
• Subjects: Analysis of Variance; Behavior; Behavioral Science and Psychology; Brief Communication; Cognitive Psychology; Confidence Intervals; Psychology; Research Design; Research methodology; Statistics; Confidence intervals; Within-subject designs; Mean plots; Statistical inference; Statistics
• ISSN: 1554-3528; 1554-3528
• DOI: 10.3758/s13428-013-0441-z

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.