CoChat
Sign Up
Cited by 826Meta-analysis and systematic reviewsPsychology Research and BibliometricsStatistical Methods in Epidemiology

The DOI matches its Crossref record; 31 of the 32 references it cites were found in a registry or an index.

Effect Size Guidelines, Sample Size Calculations, and Statistical Power in Gerontology

Open access
Brydges, Christopher R·2019·Innovation in Aging
DOI 10.1093/geroni/igz036PMC PMC6736231
Open this paper in CoChat — free accountOpen PDF

Abstract

Background and Objectives: Researchers typically use Cohen’s guidelines of Pearson’s r = .10, .30, and .50, and Cohen’s d = 0.20, 0.50, and 0.80 to interpret observed effect sizes as small, medium, or large, respectively. However, these guidelines were not based on quantitative estimates and are only recommended if field-specific estimates are unknown. This study investigated the distribution of effect sizes in both individual differences research and group differences research in gerontology to provide estimates of effect sizes in the field. Research Design and Methods: Effect sizes (Pearson’s r, Cohen’s d, and Hedges’ g) were extracted from meta-analyses published in 10 top-ranked gerontology journals. The 25th, 50th, and 75th percentile ranks were calculated for Pearson’s r (individual differences) and Cohen’s d or Hedges’ g (group differences) values as indicators of small, medium, and large effects. A priori power analyses were conducted for sample size calculations given the observed effect size estimates. Results: Effect sizes of Pearson’s r = .12, .20, and .32 for individual differences research and Hedges’ g = 0.16, 0.38, and 0.76 for group differences research were interpreted as small, medium, and large effects in gerontology. Discussion and Implications: Cohen’s guidelines appear to overestimate effect sizes in gerontology. Researchers are encouraged to use Pearson’s r = .10, .20, and .30, and Cohen’s d or Hedges’ g = 0.15, 0.40, and 0.75 to interpret small, medium, and large effects in gerontology, and recruit larger samples.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/geroni/igz036

Cites

31 of 31 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1. Meta-analysis inclusion flow chart for effect size distribution analysis.
Figure 1. Meta-analysis inclusion flow chart for effect size distribution analysis.CC BY · PubMed Central
Figure 2. (A) The distributions of correlations (Pearson’s r). The dashed red lines represent the 25th, 50th, and 75th percentiles, which correspond to small (Pearson’s r = .12), medium (Pearson’s r = .20), and large (Pearson’s r = .32) effects. (B) The distributions of Hedges’ g. The dashed red lines represent the 25th, 50th, and 75th percentiles, which correspond to small (Hedges’ g = 0.16), medium (Hedges’ g = 0.38), and large (Hedges’ g = 0.76) effects. The purple lines in each panel represent the a priori power achieved by the median sample size of the included studies across effect sizes.
Figure 2. (A) The distributions of correlations (Pearson’s r). The dashed red lines represent the 25th, 50th, and 75th percentiles, which correspond to small (Pearson’s r = .12), medium (Pearson’s r = .20), and large (Pearson’s r = .32) effects. (B) The distributions of Hedges’ g. The dashed red lines represent the 25th, 50th, and 75th percentiles, which correspond to small (Hedges’ g = 0.16), medium (Hedges’ g = 0.38), and large (Hedges’ g = 0.76) effects. The purple lines in each panel represent the a priori power achieved by the median sample size of the included studies across effect sizes.CC BY · PubMed Central
Figure 3. (A) One-sided contour-enhanced funnel plot for individual differences research. (B) One-sided contour-enhanced funnel plot for group differences research. (C) One-sided contour-enhanced funnel plot for group differences research in biomedical gerontology. (D) One-sided contour-enhanced funnel plot for group differences research in psychosocial gerontology.
Figure 3. (A) One-sided contour-enhanced funnel plot for individual differences research. (B) One-sided contour-enhanced funnel plot for group differences research. (C) One-sided contour-enhanced funnel plot for group differences research in biomedical gerontology. (D) One-sided contour-enhanced funnel plot for group differences research in psychosocial gerontology.CC BY · PubMed Central
Figure 4. Density plots illustrating the distribution of Hedges’ g, based on study categorization as biomedical (pink) or psychosocial (turquoise). The distributions display the larger average effect size of the psychosocial studies.
Figure 4. Density plots illustrating the distribution of Hedges’ g, based on study categorization as biomedical (pink) or psychosocial (turquoise). The distributions display the larger average effect size of the psychosocial studies.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 32 references

Research works printed but not linked: 1

  1. Morey, 2016, Why most of psychology is unfalsifiable

Cited by

Sorted by citations

Items 401–500 of 825

Related

See all

Metadata

Authors
Brydges, C. R.
Affiliations
Colorado State University (US)
Corresponding author
Brydges, Christopher R
ORCID
Brydges, Christopher R
Venue
Innovation in Aging
Publisher
Oxford University Press (OUP)
Published
2019-08-01
Volume
3
Issue
4
Pages
igz036-igz036
ISSN
2399-5300 (ISSN-L)
DOI
10.1093/geroni/igz036
PMC
PMC6736231
OpenAlex
W2972140183
Cited by
826
References
32
Citations by year
2026: 212 · 2025: 212 · 2024: 168 · 2023: 90 · 2022: 68 · 2021: 56 · 2020: 18 · 2019: 1
FWCI
23.92
Type
journal article
Language
en
Open access
Licence
Locations
  • Innovation in Aging (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (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 in Epidemiology
Keywords
effect size interpretation, Cohen's d, Hedges' g, Pearson correlation, sample size determination, statistical power, gerontology, individual differences, group differences, meta-analysis, effect size distribution, aging research

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