Using randomization techniques to analyse behavioural data
Article Abstract:
Valuable information contained in the data from behavioral studies is often lost due to the use of non-parametric methods of analyses. Results from the Kruskal-Wallis non-parametric ANOVA and randomization tests for two behavioral data sets show that randomization tests are more efficient. The smaller effect sizes in the data are easily detected by randomization tests. The variance calculated around the P-value decreases as the number of replications increases from 500 to 10,000. At least 5,000 replications are recommended for the randomization tests.
Publication Name: Animal Behaviour
Subject: Zoology and wildlife conservation
ISSN: 0003-3472
Year: 1996
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Using randomization techniques to analyse fluctuating asymmetry data
Article Abstract:
Randomization methods are proposed for fluctuating asymmetry data analysis. Fluctuating asymmetry data in evolutionary and ecological research often have statistical problems in normal distribution or differences in variances. Randomization tests are more accurate than standard parametric tests in terms of error minimization since it is more suitable for small sample sizes.
Publication Name: Animal Behaviour
Subject: Zoology and wildlife conservation
ISSN: 0003-3472
Year: 1997
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Assessing the robustness of randomization tests: examples from behavioral studies
Article Abstract:
A new study evaluates the use of randomization tests in behavioral studies and suggests that Monte Carlo methods should be used in some cases.
Publication Name: Animal Behaviour
Subject: Zoology and wildlife conservation
ISSN: 0003-3472
Year: 2001
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