Effect sizes for nonparametric tests
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Abstract
Effect size measures are important complements to P values, providing information about the magnitude and practical relevance of research findings. While widely discussed in the context of parametric tests, effect size estimation for nonparametric tests remains less explored. This article reviews standardized effect size measures applicable to four common nonparametric tests: Mann-Whitney, Wilcoxon signed-rank, Kruskal-Wallis, and Friedman. Commonly suggested classifications for these effect sizes are also discussed. This article aims to support researchers in reporting and interpreting effect sizes more effectively in nonparametric contexts.
Citation impact
42
total citations
- FWCI
- 43.07
- Percentile
- 100%
- References
- 21
Citations per year
Authors
1Topics & keywords
Topics
Keywords
- Nonparametric statistics
- Wilcoxon signed-rank test
- Context (archaeology)
- Parametric statistics
- Statistical hypothesis testing
- Estimation
- Relevance (law)
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