What Are Effect Sizes and Why Do We Need Them?
Abstract
Effect sizes are quantitative indexes of the relations between variables found in research studies. They can provide a broadly understandable summary of research findings that can be used to compare different studies or summarize results across studies. Unlike statistical significance (p values), effect sizes represent strength of relationships without regard to sample size. Three families of effect sizes are widely used: the standardized mean difference family, the standardized regression coefficient family, and the odds ratio family.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Variation in samples of people across studies can limit the comparability of effect sizes to a degree.
“The studies in our dataset, though, come from different samples of people—some look at doctors37–39, others at crowdworkers4,6,34 and still others at students13,40,41—and this variation can limit the comparability of the effect sizes to a degree36.”
From When combinations of humans and AI are useful: A systematic review and meta-analysis (2024) · cites this paper as [36]
Cites
Distribution Theory for Glass's Estimator of Effect Size and Related Estimators
Hedges, L. V. (1981) · Journal of Educational Statistics · doi:10.2307/1164588 · Cited by 5,695 · see citing works
Self-citationLipsey, M. W., & Wilson, D. B. (1993) · American Psychologist · doi:10.1037/0003-066x.48.12.1181 · Cited by 2,033 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
To read or not to read: a meta-analysis of print exposure from infancy to early adulthood
Mol, S. E., & Bus, A. G. (2011) · Psychological Bulletin · doi:10.1037/a0021890 · Cited by 1,299 · see citing works
Interpreting effect sizes of education interventions
Kraft, M. A. (2020) · Educational Researcher · doi:10.3102/0013189x20912798 · Cited by 1,281 · see citing works
When combinations of humans and AI are useful: A systematic review and meta-analysis
Vaccaro, M., Almaatouq, A., & Malone, T. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-02024-1 · Cited by 570 · see citing works
“The studies in our dataset, though, come from different samples of people—some look at doctors 37–39 , others at crowdworkers 4,6,34 and still others at students 13,40,41 —and this variation can limit the comparability of the effect sizes to a degree 36 .”
Sex Differences in Romantic Attachment: A Meta-Analysis
Del Giudice, M. (2011) · Personality and Social Psychology Bulletin · doi:10.1177/0146167210392789 · Cited by 441 · see citing works
The Distance Between Mars and Venus: Measuring Global Sex Differences in Personality
Del Giudice, M., Booth, T., & Irwing, P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0029265 · Cited by 256 · see citing works
- Authors
- Hedges, L. V.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Hedges, Larry V
- ORCID
- Hedges, Larry V
- Venue
- Child Development Perspectives
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-11-24
- Volume
- 2
- Issue
- 3
- Pages
- 167-171
- ISSN
- 1750-8592 (ISSN-L)
- 1750-8606
- OpenAlex
- W2138862510
- Cited by
- 123
- References
- 2
- Citations by year
- 2026: 8 · 2025: 7 · 2024: 8 · 2023: 6 · 2022: 8 · 2021: 6 · 2020: 14 · 2019: 6 · 2018: 8 · 2017: 6 · 2016: 8 · 2015: 7 · 2014: 5 · 2013: 5 · 2012: 10
- FWCI
- 4.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Child Development Perspectives (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
- Social Sciences › Education › Educational Research and Methods
- Keywords
- effect size, standardized mean difference, standardized regression coefficients, odds ratio, statistical significance, p-values, meta-analysis, evidence synthesis, sample size
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
