The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Limitations of PET-PEESE and Other Meta-Analysis Methods
Open accessAbstract
A novel meta-regression method, precision-effect test and precision-effect estimate with standard errors (PET-PEESE), predicts and explains recent high-profile failures to replicate in psychology. The central purpose of this article is to identify the limitations of PET-PEESE for application to social/personality psychology. Using typical conditions found in social/personality research, our simulations identify three areas of concern. PET-PEESE performs poorly in research areas where there are only a few studies, all studies use small samples, and where there is very high heterogeneity of results from study to study. Nonetheless, the statistical properties of conventional meta-analysis approaches are much worse than PET-PEESE under these same conditions. Our simulations suggest alterations to conventional research practice and ways to moderate PET-PEESE weaknesses.
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“Overall, PET-PEESE has a low false positive rate, but its estimation of the effect size tends to be imprecise with a sample size of small, heterogeneous studies, resulting in large standard errors, such that 'if all studies are small, PET-PEESE has little power to identify a genuine empirical effect' (p. 590, Stanley, 2017)5.”
From Managing the terror of publication bias: A comprehensive p-curve analysis of the Terror Management Theory literature (2023) · cites this paper as Stanley, 2017
In the citing paper
“However, this counterintuitive finding may be explained by the fact that PET is prone to producing imprecise and biased estimates under high heterogeneity, small sample sizes, and a large proportion of p-hacking (Stanley & Doucouliagos, 2014; Stanley 2017; Carter et al., 2019).”
From Managing the terror of publication bias: A comprehensive p-curve analysis of the Terror Management Theory literature (2023) · cites this paper as Stanley 2017
In the citing paper
“However, when effects are highly heterogeneous and when sample sizes are small, the PET-PEESE analysis is known to yield imprecise estimates (Stanley & Doucouliagos, 2014; Stanley, 2017; Carter et al., 2019).”
From Managing the terror of publication bias: A comprehensive p-curve analysis of the Terror Management Theory literature (2023) · cites this paper as Stanley, 2017
In the citing paper
“Furthermore, its estimate should be interpreted with caution in small meta-analyses (with 20 studies or less; Stanley, 2017).”
From Please don't stop the music: A meta-analysis of the cognitive and academic benefits of instrumental musical training in childhood and adolescence (2022) · cites this paper as Stanley, 2017
In the citing paper
“Regarding the adjustment of the effect, the original PET-PEESE (which assumes independence) performed worse with smaller true effects and higher heterogeneity, consistently underestimating the true effect.”
From Please don't stop the music: A meta-analysis of the cognitive and academic benefits of instrumental musical training in childhood and adolescence (2022) · cites this paper as Stanley, 2017
In the citing paper
“There are two main threats to the validity of meta-analytic results: the systematic omission of studies (e.g., publication bias suppressing studies with null results36,37), and the flexible selection of analysis approaches within each study inflating the rate of false positives (e.g., p-hacking38).”
From Accuracy prompts are a replicable and generalizable approach for reducing the spread of misinformation (2022) · cites this paper as [37]
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Metadata
- Authors
- Stanley, T. D.
- Affiliations
- Hendrix College (US)
- Corresponding author
- Stanley, T. D.
- ORCID
- Stanley, T. D.
- Venue
- Social Psychological and Personality Science
- Publisher
- SAGE Publications
- Published
- 2017-02-28
- Volume
- 8
- Issue
- 5
- Pages
- 581-591
- ISSN
- 1948-5506 (ISSN-L)
- 1948-5514
- OpenAlex
- W2591641564
- Semantic Scholar
- 62d9746bdeace29af787162583753de042a82d8a
- Cited by
- 229
- References
- 37
- Citations by year
- 2026: 23 · 2025: 29 · 2024: 21 · 2023: 33 · 2022: 25 · 2021: 27 · 2020: 21 · 2019: 27 · 2018: 18 · 2017: 5
- FWCI
- 17.48
- Type
- journal article
- Language
- en
- Open access
- green
- figshare.com
- Locations
- Social Psychological and Personality Science (publishedVersion)
- Figshare (submittedVersion, cc-by)
- 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
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- meta-regression, replication failure, small sample bias, effect size heterogeneity, meta-analysis limitations, social-personality psychology, simulation study
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.
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