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Cited by 220Meta-analysis and systematic reviewsPsychology Research and Bibliometricsscientometrics and bibliometrics research

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.

Conducting Meta-Analyses Based on p Values: Reservations and Recommendations for Applying p -Uniform and p -Curve

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van Aert, Robbie C. M., Wicherts, Jelte M., van Assen, Marcel A. L. M.·2016·Perspectives on Psychological Science
DOI 10.1177/1745691616650874PMC PMC5117126
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Abstract

Because of overwhelming evidence of publication bias in psychology, techniques to correct meta-analytic estimates for such bias are greatly needed. The methodology on which the p-uniform and p-curve methods are based has great promise for providing accurate meta-analytic estimates in the presence of publication bias. However, in this article, we show that in some situations, p-curve behaves erratically, whereas p-uniform may yield implausible estimates of negative effect size. Moreover, we show that (and explain why) p-curve and p-uniform result in overestimation of effect size under moderate-to-large heterogeneity and may yield unpredictable bias when researchers employ p-hacking. We offer hands-on recommendations on applying and interpreting results of meta-analyses in general and p-uniform and p-curve in particular. Both methods as well as traditional methods are applied to a meta-analysis on the effect of weight on judgments of importance. We offer guidance for applying p-uniform or p-curve using R and a user-friendly web application for applying p-uniform.

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Cites

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Figures

Fig. 1. Probability-probability (P-P) plot for a meta-analysis of 20 studies with large heterogeneity.
Fig. 1. Probability-probability (P-P) plot for a meta-analysis of 20 studies with large heterogeneity.CC BY · PubMed Central
Fig. 2. Values for Kolmogorov-Smirnov (KS) test statistics in implementation of p-curve and p-uniform for the example with three observed effect sizes and p values close to .05. D stat = test statistics of KS test.
Fig. 2. Values for Kolmogorov-Smirnov (KS) test statistics in implementation of p-curve and p-uniform for the example with three observed effect sizes and p values close to .05. D stat = test statistics of KS test.CC BY · PubMed Central
Fig. 3. Effect size estimates in p-uniform and fixed-effect meta-analysis in case of four types of p-hacking. FE = fixed-effect; DV = dependent variable.
Fig. 3. Effect size estimates in p-uniform and fixed-effect meta-analysis in case of four types of p-hacking. FE = fixed-effect; DV = dependent variable.CC BY · PubMed Central
Fig. A1. Computation of conditional p values for Effect 3 (q3) for three effect sizes: δ = 0; δ = 0.5 (true effect size); and δ = 0.748 (estimate of fixed-effect meta-analysis). Critical value on Cohen’s d scale is denoted by dcv and observed effect size is denoted by dobs.
Fig. A1. Computation of conditional p values for Effect 3 (q3) for three effect sizes: δ = 0; δ = 0.5 (true effect size); and δ = 0.748 (estimate of fixed-effect meta-analysis). Critical value on Cohen’s d scale is denoted by dcv and observed effect size is denoted by dobs.CC BY · PubMed Central
Fig. A2. Observed conditional p values (solid black lines) and conditional p values under uniformity (dashed gray lines) for the example with three observed effect sizes. The three panels refer to the conditional p values for the p-uniform hypothesis test of no effect (δ = 0), p-uniform effect size estimate (δ = 0.5), and effect size obtained by fixed-effect (FE) meta-analysis (δ = 0.748).
Fig. A2. Observed conditional p values (solid black lines) and conditional p values under uniformity (dashed gray lines) for the example with three observed effect sizes. The three panels refer to the conditional p values for the p-uniform hypothesis test of no effect (δ = 0), p-uniform effect size estimate (δ = 0.5), and effect size obtained by fixed-effect (FE) meta-analysis (δ = 0.748).CC BY · PubMed Central
Fig. A3. Conditional p values as a function of true effect size (x axis) for each of the three observed effect sizes in the example. Effect sizes zero (δ = 0), true effect size (δ = 0.5), and estimated by fixed-effect meta-analysis (δ = 0.748) are indicated by vertical lines.
Fig. A3. Conditional p values as a function of true effect size (x axis) for each of the three observed effect sizes in the example. Effect sizes zero (δ = 0), true effect size (δ = 0.5), and estimated by fixed-effect meta-analysis (δ = 0.748) are indicated by vertical lines.CC BY · PubMed Central

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Citations

Cites

Show all 54 references

Research works printed but not linked: 4

  1. American Psychological Association, 2010, Publication manual
  2. Augusteijn H. E. M. (2015). The effect of publication bias on the Q test and assessment of heterogeneity (Unpublished master’s thesis). Tilburg University, Tilburg, the Netherlands.
  3. Raudenbush S. W., 2009, The handbook of research synthesis and meta-analysis, 295
  4. van Aert R. C. M., 2016, Estimating effect size in meta-analysis in the presence of publication bias and questionable research practices

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Metadata

Authors
van Aert, R. C. M., Wicherts, J. M., & van Assen, M. A. L. M.
Affiliations
  • Tilburg University (NL)
  • Utrecht University (NL)
Corresponding author
van Aert, Robbie C. M.
ORCID
Venue
Perspectives on Psychological Science
Publisher
SAGE Publications
Published
2016-09
Volume
11
Issue
5
Pages
713-729
ISSN
  • 1745-6916 (ISSN-L)
  • 1745-6924
DOI
10.1177/1745691616650874
PMC
PMC5117126
OpenAlex
W2526603989
Cited by
219
References
54
Citations by year
2026: 12 · 2025: 13 · 2024: 24 · 2023: 22 · 2022: 28 · 2021: 22 · 2020: 25 · 2019: 23 · 2018: 20 · 2017: 27 · 2016: 3
FWCI
22.73
Type
journal article
Language
en
Open access
Licence
Locations
  • Perspectives on Psychological Science (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • Research portal (Tilburg University) (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
  • OSF Preprints (OSF Preprints) (submittedVersion)
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
p-curve, publication bias, meta-analysis, effect size estimation, p-hacking, heterogeneity, effect size overestimation, R package, web application
MeSH terms
Data Interpretation, Statistical, Humans, Psychology, Software, Meta-Analysis as Topic, Models, Statistical, Publication Bias, Internet

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