Behavioral Ecology Advance Access originally published online on February 24, 2008
Behavioral Ecology 2008 19(3):690-693; doi:10.1093/beheco/arn020
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© The Author 2008. Published by Oxford University Press on behalf of the International Society for Behavioral Ecology. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org
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Time for some a priori thinking about post hoc testing
a Institute of Biomedical Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK b Faculty of Veterinary Medicine, University of Montréal, PO Box 5000, St-Hyacinthe, Québec, Canada J2S 7C6
Address correspondence to G.D. Ruxton. E-mail: g.ruxton@bio.gla.ac.uk.
Received 2 December 2007; revised 9 January 2008; accepted 10 January 2008.
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INTRODUCTION |
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Researchers are commonly in a situation, often after an experiment, where they want to compare the central tendency of some measure across a number of groups. If the number of groups is simply 2, then there is little controversy as to the appropriate analysis, with normally a t-test or a nonparametric equivalent being adopted. If the number of groups is greater than 2, most elementary statistical textbooks suggest performing an analysis of variance (ANOVA) to test the null hypothesis that all the groups are the same and, if this null hypothesis is rejected, implementing some post hoc testing to identify which groups are significantly different from which other groups.
However, as readers and reviewers of scientific papers in behavioral science, we have noted a great diversity of approaches when comparing more than 2 groups often with little or no justification for the adoption of a specific approach. Hence, our
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WHAT DO RESEARCHERS CURRENTLY DO? |
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ASPECTS OF GOOD PRACTICE |
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Researchers should strive for planned comparisons
Implementing a set of planned comparisons
Implementing a set of unplanned comparisons
The nonparametric case
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THE CASE FOR A CHANGE IN BEHAVIOR AMONG RESEARCHERS |
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CONCLUSION |
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