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Cited by 767Meta-analysis and systematic reviewsStatistical Methods in EpidemiologyStatistical Methods and Bayesian Inference

The DOI matches its Crossref record; 16 of the 17 references it cites were found in a registry or an index.

Meta-Analysis and Subgroups

Borenstein, Michael, Higgins, Julian P. T.·2013·Prevention Science
DOI 10.1007/s11121-013-0377-7
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Abstract

Subgroup analysis is the process of comparing a treatment effect for two or more variants of an intervention-to ask, for example, if an intervention's impact is affected by the setting (school versus community), by the delivery agent (outside facilitator versus regular classroom teacher), by the quality of delivery, or if the long-term effect differs from the short-term effect. While large-scale studies often employ subgroup analyses, these analyses cannot generally be performed for small-scale studies, since these typically include a homogeneous population and only one variant of the intervention. This limitation can be bypassed by using meta-analysis. Meta-analysis allows the researcher to compare the treatment effect in different subgroups, even if these subgroups appear in separate studies. We discuss several statistical issues related to this procedure, including the selection of a statistical model and statistical power for the comparison. To illustrate these points, we use the example of a meta-analysis of obesity prevention.

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Metadata

Authors
Borenstein, M., & Higgins, J. P. T.
Affiliations
  • Biostat (United States) (US)
  • University of Bristol (GB)
Corresponding author
Borenstein, Michael
ORCID
Venue
Prevention Science
Publisher
Springer Science and Business Media LLC
Published
2013-03-13
Volume
14
Issue
2
Pages
134-143
ISSN
  • 1389-4986 (ISSN-L)
  • 1573-6695
DOI
10.1007/s11121-013-0377-7
OpenAlex
W2032737645
Cited by
767
References
17
Citations by year
2026: 68 · 2025: 95 · 2024: 134 · 2023: 124 · 2022: 94 · 2021: 86 · 2020: 45 · 2019: 31 · 2018: 19 · 2017: 29 · 2016: 14 · 2015: 12 · 2014: 8 · 2013: 3
FWCI
13.59
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)
Locations
  • Prevention Science (publishedVersion)
  • PubMed (publishedVersion)
  • Bristol Research (University of Bristol) (submittedVersion)
Funders
  • National Institutes of Health (5r44da019280-03, 5r44da022799-03, 4r44da025366-02)
  • Medical Research Council
  • National Institute on Drug Abuse (DA022799, DA019280, DA025366)
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords
subgroup analysis, meta-analysis, treatment effect heterogeneity, statistical power, statistical models, obesity prevention, delivery agents
MeSH terms
Data Interpretation, Statistical, Humans, Models, Theoretical, Obesity, Morbid

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