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Cited by 2,977Meta-analysis and systematic reviewsStatistical Methods and Bayesian InferenceReliability and Agreement in Measurement

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.

Hedges, Larry V., Vevea, Jack L.·1998·Psychological Methods
DOI 10.1037/1082-989x.3.4.486
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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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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
Publisher
American Psychological Association (APA)
Published
1998-12
Volume
3
Issue
4
Pages
486-504
ISSN
  • 1082-989X (ISSN-L)
  • 1939-1463
DOI
10.1037/1082-989x.3.4.486
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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