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The effect sizes were adjusted according to Hedges and Olkin (1985) to account for bias in sample sizes.
“We adjusted the effect sizes (ES) according to Hedges and Olkin, (1985) to account for bias in sample sizes, according to this”
From A Meta-Analysis of Ten Learning Techniques (2021) · cites this paper as Hedges and Olkin, (1985)
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- Authors
- Hedges, L. V., & Olkin, I.
- Affiliations
- University of Chicago (US)
- Stanford University (US)
- ORCID
- Larry Vernon Hedges
- Venue
- Elsevier eBooks
- Publisher
- Elsevier
- Published
- 1985
- Pages
- 47-74
- OpenAlex
- W2506046274
- Cited by
- 7
- References
- 0
- Citations by year
- 2026: 2 · 2023: 1 · 2022: 1
- FWCI
- 0.00
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Elsevier eBooks (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- effect size estimation, standardized mean difference, correlation coefficient
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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