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The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective
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In the practice of data analysis, there is a conceptual distinction between hypothesis testing, on the one hand, and estimation with quantified uncertainty on the other. Among frequentists in psychology, a shift of emphasis from hypothesis testing to estimation has been dubbed "the New Statistics" (Cumming 2014). A second conceptual distinction is between frequentist methods and Bayesian methods. Our main goal in this article is to explain how Bayesian methods achieve the goals of the New Statistics better than frequentist methods. The article reviews frequentist and Bayesian approaches to hypothesis testing and to estimation with confidence or credible intervals. The article also describes Bayesian approaches to meta-analysis, randomized controlled trials, and power analysis.
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“A Bayesian approach was selected because it estimates the full probability distribution of treatment effects rather than relying on binary significance testing, allowing more informative interpretation of effect sizes and associated uncertainty [40, 41].”
From The Effect of Different Psychological Interventions on Athletes' Competitive Anxiety: A Systematic Review and Bayesian Network Meta-Analysis. (2026) · cites this paper as [40]
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Metadata
- Authors
- Kruschke, J. K., & Liddell, T. M.
- Affiliations
- Indiana University Bloomington (US)
- Corresponding author
- Kruschke, John K.
- ORCID
- Kruschke, John K.
- Venue
- Psychonomic Bulletin & Review
- Published
- 2017-02-07
- Volume
- 25
- Issue
- 1
- Pages
- 178-206
- ISSN
- 1069-9384 (ISSN-L)
- 1531-5320
- OpenAlex
- W3124625789
- Cited by
- 1,288
- References
- 104
- Citations by year
- 2026: 137 · 2025: 171 · 2024: 156 · 2023: 133 · 2022: 153 · 2021: 186 · 2020: 133 · 2019: 98 · 2018: 88 · 2017: 32
- FWCI
- 66.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Psychonomic Bulletin & Review (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- OSF Preprints (OSF Preprints) (submittedVersion)
- 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
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- new statistics, Bayesian analysis, hypothesis testing, confidence intervals, credible intervals, meta-analysis, power analysis, randomized controlled trials
- MeSH terms
- Bayes Theorem, Humans, Research Design, Statistics as Topic, Meta-Analysis as Topic, Uncertainty
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 ›
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