Those confounded moderators in meta-analysis: good, bad, and ugly
Abstract
One of the more revealing aspects of meta-analysis is the relationship between effect sizes and moderator variables representing differences among studies in their methods, samples, and interventions. However, interesting moderator variables are generally related to each other as well as to effect sizes. This confounding among moderator variables can make the results of any analysis focusing on a single moderator variable misleading. Despite the ambiguity of such results, this form of analysis is common in meta-analytic studies of intervention. The hazards and complexities of investigating and interpreting confounded moderator variables are illustrated in this article by the author's examining the difference in effect sizes associated with randomized versus nonrandomized designs in a large meta-analytic database of delinquency intervention studies.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The results of moderator analysis should be interpreted with caution due to the small number of studies included in the meta-analysis and covarying moderator variables across studies.
“The results of moderator analysis should be interpreted with caution due to the small number of studies included in the meta-analysis and covarying moderator variables across studies (Lipsey, 2003), which may cause misleading results in analyses focusing on single moderator variables.”
From A Meta-Analysis of the Effects of Mental Contrasting With Implementation Intentions on Goal Attainment (2021) · cites this paper as Lipsey, 2003
The citation lists haven’t been fetched yet
References 14 · Cited by 283
- Authors
- Lipsey, M. W.
- Affiliations
- Vanderbilt University (US)
- Corresponding author
- Lipsey, Mark W.
- ORCID
- Lipsey, Mark W.
- Venue
- The ANNALS of the American Academy of Political and Social Science
- Publisher
- SAGE Publications
- Published
- 2003-05
- Volume
- 587
- Issue
- 1
- Pages
- 69-81
- ISSN
- 0002-7162 (ISSN-L)
- 1552-3349
- OpenAlex
- W2058738343
- Cited by
- 283
- References
- 14
- Citations by year
- 2026: 10 · 2025: 5 · 2024: 9 · 2023: 21 · 2022: 14 · 2021: 22 · 2020: 20 · 2019: 13 · 2018: 13 · 2017: 9 · 2016: 14 · 2015: 18 · 2014: 16 · 2013: 9 · 2012: 15
- FWCI
- 9.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Annals of the American Academy of Political and Social Science (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 › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
- Keywords
- meta-analysis, effect size, moderator analysis, delinquency intervention, intervention effectiveness
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review