The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Fixed-and random-effects models in meta-analysis.
Abstract
There are 2 families of statistical procedures in meta-analysis: fixed- and randomeffects procedures. They were developed for somewhat different inference goals: making inferences about the effect parameters in the studies that have been observed versus making inferences about the distribution of effect parameters in a population of studies from a random sample of studies. The authors evaluate the performance of confidence intervals and hypothesis tests when each type of statistical procedure is used for each type of inference and confirm that each procedure is best for making the kind of inference for which it was designed. Conditionally random-effects procedures (a hybrid type) are shown to have properties in between those of fixed- and random-effects procedures. The use of quantitative methods to summarize the results of several empirical research studies, or metaanalysis, is now widely used in psychology, medicine, and the social sciences. Meta-analysis usually involves describing the results of each study by means of a numerical index (an estimate of effect size, such as a correlation coefficient, a standardized mean difference, or an odds ratio) and then combining these estimates across studies to obtain a summary. Two somewhat different statistical models have been developed for inference about average effect size from a collection of studies, called the fixed-effects and random-effects models. (A third alternative, the mixedeffects model, arises in conjunction with analyses involving study-level covariates or moderator variables, which we do not consider in this article; see Hedges, 1992.) Fixed-effects models treat the effect-size parameters as fixed but unknown constants to be estimated and usually (but not necessarily) are used in conjunction with assumptions about the homogeneity of effect parameters (see, e.g., Hedges, 1982; Rosenthal & Rubin, 1982). Random-effects models treat the effectsize parameters as if they were a random sample from
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In the citing paper
“We applied random effects models (Hedges & Vevea, 1998) because they take possible differences in effect sizes among the included studies into account.”
From Blending Teacher Autonomy Support and Provision of Structure in the Classroom for Optimal Motivation: A Systematic Review and Meta-Analysis (2025) · cites this paper as Hedges & Vevea, 1998
In the citing paper
“Random effects models were utilized since we anticipated that effect sizes would vary across studies and this model approach allows for a greater degree of generalizability (Hedges & Vevea, 1998).”
From The interpersonal theory of suicide: A systematic review and meta-analysis of a decade of cross-national research. (2017) · cites this paper as Hedges & Vevea, 1998
In the citing paper
“A random effects approach produces results that generalize beyond the sample of studies actually reviewed [27].”
From Social Relationships and Mortality Risk: A Meta-analytic Review (2010) · cites this paper as [27]
In the citing paper
“This model is based on the assumption that the population effect differs randomly from study to study and accounts for within- and between-study variability [72,73]; therefore, more general inferences can be made compared with fixed-effect models.”
From Conceptualizations of cyberchondria and relations to the anxiety spectrum: Systematic review and meta-analysis (2021) · cites this paper as [73]
Citations
Cites
Meta-analysis in clinical trials
DerSimonian, R., & Laird, N. (1986) · Controlled Clinical Trials · doi:10.1016/0197-2456(86)90046-2 · Cited by 39,552
Wasserman, S. S., Hedges, L. V., & Olkin, I. (1988) · Journal of Educational Statistics · doi:10.2307/1164953 · Cited by 10,377
Self-citationDistribution 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
Self-citationMethods of Meta-Analysis: Correcting Error and Bias in Research Findings
Schmidt, F. L., & Hunter, J. E. (2015) · doi:10.4135/9781483398105 · Cited by 5,542
What do data really mean? Research findings, meta-analysis, and cumulative knowledge in psychology.
Schmidt, F. L. (1992) · American Psychologist · doi:10.1037/0003-066x.47.10.1173 · Cited by 564
The non-central chi2- and F-distributions and their applications.
PATNAIK, P. B. (1949) · PubMed · Cited by 556
How large are cognitive gender differences? A meta-analysis using !w² and d..
Hyde, J. S. (1981) · American Psychologist · doi:10.1037/0003-066x.36.8.892 · Cited by 529
Comparing effect sizes of independent studies.
Rosenthal, R., & Rubin, D. B. (1982) · Psychological Bulletin · doi:10.1037//0033-2909.92.2.500 · Cited by 406
A random effects model for effect sizes.
Hedges, L. V. (1983) · Psychological Bulletin · doi:10.1037/0033-2909.93.2.388 · Cited by 399
Self-citationEmpirical bayes meta-analysis.
Raudenbush, S. W., & Bryk, A. S. (1985) · Journal of Educational Statistics · doi:10.3102/10769986010002075 · Cited by 299
Cited by
Sorted by citations
Conducting Meta-Analyses in R with the metafor Package
Viechtbauer, W. (2010) · Journal of Statistical Software · doi:10.18637/jss.v036.i03 · Cited by 20,464
Social Relationships and Mortality Risk: A Meta-analytic Review
Holt-Lunstad, J., Smith, T. B., & Layton, J. B. (2010) · PLoS Medicine · doi:10.1371/journal.pmed.1000316 · Cited by 7,272
“Aggregate effect sizes were calculated using random effects models following confirmation of heterogeneity. A random effects approach produces results that generalize beyond the sample of studies actually reviewed”
MethodA basic introduction to fixed-effect and random-effects models for meta-analysis
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2010) · Research Synthesis Methods · doi:10.1002/jrsm.12 · Cited by 6,793
Self-citationEmotion-regulation strategies across psychopathology: A meta-analytic review
Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010) · Clinical Psychology Review · doi:10.1016/j.cpr.2009.11.004 · Cited by 6,686
Cochrane Handbook for Systematic Reviews of Interventions
Tarsilla, M. (2010) · Journal of MultiDisciplinary Evaluation · doi:10.56645/jmde.v6i14.284 · Cited by 5,232
Metadata
- Authors
- Hedges, L. V., & Vevea, J. L.
- Affiliations
- University of Chicago (US)
- University of North Carolina at Chapel Hill (US)
- ORCID
- Hedges, Larry V.
- Venue
- Psychological Methods
- Published
- 1998-12
- Volume
- 3
- Issue
- 4
- Pages
- 486-504
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W1964605289
- Semantic Scholar
- 48a2d7ae1a17b8fec9cb05a9dd68c1f2784f2ba7
- Cited by
- 2,977
- References
- 15
- Citations by year
- 2026: 120 · 2025: 127 · 2024: 164 · 2023: 176 · 2022: 159 · 2021: 226 · 2020: 194 · 2019: 163 · 2018: 164 · 2017: 188 · 2016: 146 · 2015: 148 · 2014: 160 · 2013: 120 · 2012: 101
- FWCI
- 11.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Methods (publishedVersion)
- 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
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
- Keywords
- fixed effects model, random effects models, meta-analysis, confidence intervals, hypothesis testing, effect size heterogeneity, statistical model comparison
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