| Title |
Calculating and graphing within-subject confidence intervals for ANOVA
|
|---|---|
| Published in |
Behavior Research Methods, August 2011
|
| DOI | 10.3758/s13428-011-0123-7 |
| Pubmed ID | |
| Authors |
Thom Baguley |
| Abstract |
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. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 2 | 40% |
| Japan | 2 | 40% |
| Portugal | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 40% |
| Scientists | 2 | 40% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 5 | 2% |
| United States | 4 | 2% |
| United Kingdom | 2 | <1% |
| Spain | 2 | <1% |
| Canada | 2 | <1% |
| Netherlands | 1 | <1% |
| France | 1 | <1% |
| United Arab Emirates | 1 | <1% |
| Austria | 1 | <1% |
| Other | 7 | 3% |
| Unknown | 224 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 54 | 22% |
| Researcher | 49 | 20% |
| Student > Master | 26 | 10% |
| Student > Bachelor | 24 | 10% |
| Student > Doctoral Student | 16 | 6% |
| Other | 55 | 22% |
| Unknown | 26 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 116 | 46% |
| Neuroscience | 16 | 6% |
| Agricultural and Biological Sciences | 16 | 6% |
| Engineering | 14 | 6% |
| Linguistics | 9 | 4% |
| Other | 34 | 14% |
| Unknown | 45 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 December 2021.
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#14,388,865
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Outputs from Behavior Research Methods
#1,277
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Outputs of similar age
#84,736
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Outputs of similar age from Behavior Research Methods
#6
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