The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Meta-Analysis
Abstract
The use of statistical methods to combine the results of independent empirical research studies (meta-analysis) has a long history. Meta-analytic work can be divided into two traditions: tests of the statistical significance of combined results and methods for combining estimates across studies. The principal classes of combined significance tests are reviewed, and the limitations of these tests are discussed. Fixed effects approaches treat the effect magnitude parameters to be estimated as a consequence of a model involving fixed but unknown constants. Random effects approaches treat effect magnitude parameters as if they were sampled from a universe of effects and attempt to estimate the mean and variance of the hyperpopulation of effects. Mixed models incorporate both fixed and random effects. Finally, areas of current research are summarized, including methods for handling missing data, models for publication selection, models to handle studies that are not independent, and distribution-free models for random effects.
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“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 [72]
Citations
Cites
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Field, A. P., & Gillett, R. (2010) · British Journal of Mathematical and Statistical Psychology · doi:10.1348/000711010x502733 · Cited by 1,162
Tufanaru, C., Munn, Z., Stephenson, M., & Aromataris, E. (2015) · International Journal of Evidence-Based Healthcare · doi:10.1097/xeb.0000000000000065 · Cited by 1,057
Schmidt, F. L., Oh, I., & Hayes, T. L. (2008) · British Journal of Mathematical and Statistical Psychology · doi:10.1348/000711007x255327 · Cited by 729
The power of statistical tests for moderators in meta-analysis
Hedges, L. V., & Pigott, T. D. (2004) · Psychological Methods · doi:10.1037/1082-989x.9.4.426 · Cited by 672
Self-citationESG disclosure and Firm performance: A bibliometric and meta analysis
Khan, M. A. (2022) · Research in International Business and Finance · doi:10.1016/j.ribaf.2022.101668 · Cited by 573
Metadata
- Authors
- Hedges, L. V.
- Affiliations
- University of Chicago (US)
- Corresponding author
- Hedges, Larry V.
- ORCID
- Hedges, Larry V.
- Venue
- Journal of Educational Statistics
- Published
- 1992-12
- Volume
- 17
- Issue
- 4
- Pages
- 279-296
- ISSN
- 0362-9791 (ISSN-L)
- OpenAlex
- W4231153775
- Cited by
- 186
- References
- 37
- Citations by year
- 2026: 12 · 2025: 16 · 2024: 15 · 2023: 26 · 2022: 29 · 2021: 14 · 2020: 9 · 2019: 7 · 2018: 11 · 2017: 4 · 2016: 2 · 2015: 7 · 2014: 1 · 2013: 2 · 2012: 4
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Educational Statistics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- 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 › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- meta-analysis, fixed effects model, random effects models, mixed models, missing data
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