The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Must psychologists change the way they analyze their data?
Abstract
Wagenmakers, Wetzels, Borsboom, and van der Maas (2011) argued that psychologists should replace the familiar "frequentist" statistical analyses of their data with bayesian analyses. To illustrate their argument, they reanalyzed a set of psi experiments published recently in this journal by Bem (2011), maintaining that, contrary to his conclusion, his data do not yield evidence in favor of the psi hypothesis. We argue that they have incorrectly selected an unrealistic prior distribution for their analysis and that a bayesian analysis using a more reasonable distribution yields strong evidence in favor of the psi hypothesis. More generally, we argue that there are advantages to bayesian analyses that merit their increased use in the future. However, as Wagenmakers et al.'s analysis inadvertently revealed, they contain hidden traps that must be better understood before being more widely substituted for the familiar frequentist analyses currently employed by most research psychologists.
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“Bem et al. (2011) and Richard et al. (2003) stated that effect sizes in psychology typically fall in the range of 0.2 to 0.3.”
From Using the Student's t-test with extremely small sample sizes (2013) · cites this paper as Bem et al. (2011)
In the citing paper
“However, large effect sizes are uncommon in the behavioral/psychological sciences.”
From Using the Student's t-test with extremely small sample sizes (2013) · cites this paper as Bem et al. (2011)
Citations
Cites
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
Statistical Power Analysis for the Behavioral Sciences (2nd ed.).
Lachenbruch, P. A., & Cohen, J. (1989) · Journal of the American Statistical Association · doi:10.2307/2290095 · Cited by 37,421
Jeffreys, H., Moran, P. A. P., & Chatfield, C. (1922) · Nature · doi:10.1038/109132a0 · Cited by 7,877
WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility
Lunn, D. J., Thomas, A., Best, N., & Spiegelhalter, D. J. (2000) · Statistics and Computing · doi:10.1023/a:1008929526011 · Cited by 5,397
Bayesian t tests for accepting and rejecting the null hypothesis
Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009) · Psychonomic Bulletin & Review · doi:10.3758/pbr.16.2.225 · Cited by 3,688
Exposure and affect: Overview and meta-analysis of research, 1968–1987.
Bornstein, R. F. (1989) · Psychological Bulletin · doi:10.1037/0033-2909.106.2.265 · Cited by 1,970
One Hundred Years of Social Psychology Quantitatively Described
Richard, F. D., Bond, C. F., & Stokes-Zoota, J. J. (2003) · Review of General Psychology · doi:10.1037/1089-2680.7.4.331 · Cited by 1,558 · cited 2×
“As Utts et al. (2010) argued, It is rare that we have no information about a situation before we collect data.”
BackgroundResultWagenmakers, E.-J., Wetzels, R., Borsboom, D., & van der Maas, H. L. J. (2011) · Journal of Personality and Social Psychology · doi:10.1037/a0022790 · Cited by 977
Bem, D. J. (2011) · Journal of Personality and Social Psychology · doi:10.1037/a0021524 · Cited by 893
Self-citationWhy Isn't Everyone a Bayesian?
Efron, B. (1986) · The American Statistician · doi:10.1080/00031305.1986.10475342 · Cited by 379
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Dudbridge, F. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2301.11057
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Tantaros, S. (2025) · European Journal of Developmental Psychology · doi:10.1080/17405629.2025.2498756
Walleczek, J., von Stillfried, N., Schmidt, S., Wittmann, M., Kirmse, K. A., Moll, J., & Kekecs, Z. (2025) · PLoS ONE · doi:10.1371/journal.pone.0335330 · Cited by 1
Maffeo, M. L. (2026) · Cambridge University Press eBooks · doi:10.1017/9781009322348.007
Grand manuel de parapsychologie scientifique
Évrard, R., & Royaux, J. (2025) · Dunod eBooks · doi:10.3917/dunod.evrar.2025.01.0377
Assessing Stress, Coping and Quality of Life among Refugees and Asylum Seekers in Luxembourg
Ndzebir, A. (2015) · theses.fr (ABES) · doi:10.70675/3ca3d68cz7f9cz48bcz84a5z15cc5af8d6e0
Metadata
- Authors
- Bem, D. J., Utts, J., & Johnson, W. O.
- Affiliations
- Cornell University (US)
- University of California, Irvine (US)
- Venue
- Journal of Personality and Social Psychology
- Published
- 2011-10
- Volume
- 101
- Issue
- 4
- Pages
- 716-719
- ISSN
- 0022-3514 (ISSN-L)
- 1939-1315
- OpenAlex
- W2042930386
- Cited by
- 105
- References
- 16
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 1 · 2023: 3 · 2022: 1 · 2021: 5 · 2020: 10 · 2019: 6 · 2018: 28 · 2017: 10 · 2016: 6 · 2015: 9 · 2014: 6 · 2013: 4 · 2012: 8
- FWCI
- 5.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Personality and Social Psychology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Social Sciences › Psychology › Social Psychology › Paranormal Experiences and Beliefs
- Keywords
- Bayesian analysis, frequentist statistics, prior selection, reanalysis, evidence evaluation
- MeSH terms
- Data Interpretation, Statistical, Humans, Psychology
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