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Meta-Analysis: Recent Developments in Quantitative Methods for Literature Reviews
Abstract
▪ Abstract We describe the history and current status of the meta-analytic enterprise. The advantages and historical criticisms of meta-analysis are described, as are the basic steps in a meta-analysis and the role of effect sizes as chief coins of the meta-analytic realm. Advantages of the meta-analytic procedures include seeing the “landscape” of a research domain, keeping statistical significance in perspective, minimizing wasted data, becoming intimate with the data summarized, asking focused research questions, and finding moderator variables. Much of the criticism of meta-analysis has been based on simple misunderstanding of how meta-analyses are actually carried out. Criticisms of meta-analysis that are applicable are equally applicable to traditional, nonquantitative, narrative reviews of the literature. Much of the remainder of the chapter deals with the processes of effect size estimation, the understanding of the heterogeneity of the obtained effect sizes, and the practical and scientific importance of the effect sizes obtained.
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“There was some disagreement (Table 4) whether the research question should be specific (narrowly formulated) [51, 53], or general (broadly formulated) [35, 47, 49].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [51]
In the citing paper
“The majority of articles discussed aspects general to systematic reviews including advantages and limitations of different literature sources and databases, search tools, the importance of identifying unpublished studies, literature searching techniques including how to build a search string and reporting [12, 29, 33–36, 46, 48, 50, 51, 53, 54, 57, 59–62, 67, 68].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [51]
In the citing paper
“Most articles considered the combination of RCTs and non-randomised designs [29, 35, 38, 39, 49, 51, 56, 61, 75, 81].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [51]
In the citing paper
“Two articles recommended stratifying by study design if heterogeneity is large and adjusting for study design if heterogeneity is small [51, 77].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [51]
In the citing paper
“Some authors suggested that results should be combined in a single meta-analysis only in the absence of marked heterogeneity [34, 51].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [51]
In the citing paper
“One common recommendation was to explore heterogeneity in sensitivity analyses, comparing studies stratified by design or clinical features [12, 16, 29, 34, 39, 51, 55, 56, 66, 77, 85, 100, 102].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [51]
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Metadata
- Authors
- Rosenthal, R., & DiMatteo, M. R.
- Affiliations
- University of California, Riverside (US)
- Venue
- Annual Review of Psychology
- Publisher
- Annual Reviews
- Published
- 2001-02
- Volume
- 52
- Issue
- 1
- Pages
- 59-82
- ISSN
- 0066-4308 (ISSN-L)
- 1545-2085
- OpenAlex
- W1870939480
- Cited by
- 1,780
- References
- 67
- Citations by year
- 2026: 41 · 2025: 62 · 2024: 97 · 2023: 99 · 2022: 75 · 2021: 98 · 2020: 109 · 2019: 103 · 2018: 89 · 2017: 83 · 2016: 75 · 2015: 81 · 2014: 85 · 2013: 79 · 2012: 91
- FWCI
- 7.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Psychology (publishedVersion)
- 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
- Social Sciences › Library and Information Sciences › scientometrics and bibliometrics research
- Keywords
- meta-analysis, effect size, effect size estimation, effect size heterogeneity, moderators, history of meta-analysis
- MeSH terms
- Humans, Research, Science, Meta-Analysis as Topic
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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.
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