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New Effect Size Rules of Thumb
Open accessAbstract
Recommendations to expand Cohen’s (1988) rules of thumb for interpreting effect sizes are given to include very small, very large, and huge effect sizes. The reasons for the expansion, and implications for designing Monte Carlo studies, are discussed.
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“The magnitude of the overall effect size was within the small to medium range for effect sizes (Sawilowsky 2009).”
From The Impact of Peer Assessment on Academic Performance: A Meta-analysis of Control Group Studies (2020) · cites this paper as Sawilowsky 2009
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Metadata
- Authors
- Sawilowsky, S. S.
- Affiliations
- Wayne State University (US)
- Corresponding author
- Sawilowsky, Shlomo S.
- Venue
- Journal of Modern Applied Statistical Methods
- Publisher
- Scilight Press Pty Ltd
- Published
- 2009-11-01
- Volume
- 8
- Issue
- 2
- Pages
- 597-599
- ISSN
- 1538-9472 (ISSN-L)
- OpenAlex
- W1556779599
- Cited by
- 3,254
- References
- 16
- Citations by year
- 2026: 295 · 2025: 328 · 2024: 358 · 2023: 405 · 2022: 449 · 2021: 456 · 2020: 341 · 2019: 315 · 2018: 200 · 2017: 92 · 2016: 5 · 2015: 2 · 2014: 1 · 2013: 4
- FWCI
- 0.41
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Journal of Modern Applied Statistical Methods (publishedVersion)
- Human Biology (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- effect size, sample size determination
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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