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

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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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Authors: Borenstein, M., & Higgins, J. P. T.
Affiliations: Biostat (United States) (US)
University of Bristol (GB)
Corresponding author: Borenstein, Michael
ORCID: Borenstein, Michael
Higgins, Julian P. T.
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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