| Title |
Error bars in within-subject designs: a comment on Baguley (2012)
|
|---|---|
| Published in |
Behavior Research Methods, January 2014
|
| DOI | 10.3758/s13428-013-0441-z |
| Pubmed ID | |
| Authors |
Denis Cousineau, Fearghal O’Brien |
| Abstract |
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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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 3% |
| United Kingdom | 2 | 2% |
| Switzerland | 1 | <1% |
| Netherlands | 1 | <1% |
| Germany | 1 | <1% |
| Sweden | 1 | <1% |
| New Zealand | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 109 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 28 | 23% |
| Researcher | 17 | 14% |
| Student > Bachelor | 16 | 13% |
| Professor > Associate Professor | 9 | 8% |
| Student > Master | 9 | 8% |
| Other | 29 | 24% |
| Unknown | 12 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 68 | 57% |
| Neuroscience | 6 | 5% |
| Agricultural and Biological Sciences | 5 | 4% |
| Computer Science | 4 | 3% |
| Medicine and Dentistry | 4 | 3% |
| Other | 15 | 13% |
| Unknown | 18 | 15% |
Attention Score in Context
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