Cited by 1,288Statistical Methods and Bayesian InferenceMeta-analysis and systematic reviewsProbability and Statistical Research

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The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective

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Kruschke, John K., Liddell, Torrin M.·2018·Psychonomic Bulletin & Review

DOI 10.3758/s13423-016-1221-4

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Abstract

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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Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,603
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
Bayesian Data Analysis
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Bayes factors
Kass, R. E., & Raftery, A. E. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476572 · Cited by 12,558
The file drawer problem and tolerance for null results.
Rosenthal, R. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.3.638 · Cited by 9,068 · cited 1×
“But scientific journals (i.e., reviewers and editors) are reluctant to publish nonsignificant results (e.g., Rosenthal, 1979).”
Statistical Methods for Psychology.
Gudgeon, A. C., & Howell, D. C. (1994) · Journal of the Royal Statistical Society Series D (The Statistician) · doi:10.2307/2348956 · Cited by 8,277
The ASA Statement on p -Values: Context, Process, and Purpose
Wasserstein, R. L., & Lazar, N. A. (2016) · The American Statistician · doi:10.1080/00031305.2016.1154108 · Cited by 6,306 · cited 2×
“Among the most recent and prominent cautions against NHST is a statement from the American Statistical Association (ASA; Wasserstein & Lazar, 2016), which featured six principles for properly interpreting p values.”
Applied Nonparametric Statistics
Wozniak, P. J., & Daniel, W. W. (1991) · Technometrics · doi:10.2307/1268795 · Cited by 5,008
JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling
Plummer, M. (2003) · Cited by 4,720
The earth is round (p < .05).
Cohen, J. (1994) · American Psychologist · doi:10.1037/0003-066x.49.12.997 · Cited by 4,003

Show all 104 references

Research works printed but not linked: 4

Allenby, G.M., Bakken, D.G., & Rossi, P.E. (2004). The hierarchical Bayesian revolution: How Bayesian methods have changed the face of marketing research. Marketing Research, 16, 20–25.
Jeffreys, H. (1961). Theory of probability Oxford. UK: Oxford University Press.
Mayo, D.G. (2016). Don’t throw out the error control baby with the bad statistics bathwater: A commentary. The American Statistician. Retrieved from 10.1080/00031305.2016.1154108#tabModule . · DOI
Meehl, P.E. (1997). The problem is epistemology, not statistics: Replace significance tests by confidence intervals and quantify accuracy of risky numerical predictions, What if there Were no Significance Tests, 395–425, Mahwah, NJ, Erlbaum Harlow, L. L., Mulaik, S. A., & Steiger, J. H. (Eds.)

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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
Publisher: Springer Science and Business Media LLC
Published: 2017-02-07
Volume: 25
Issue: 1
Pages: 178-206
ISSN: 1069-9384 (ISSN-L)
1531-5320
DOI: 10.3758/s13423-016-1221-4
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
Licence: www.springer.com/tdm (unspecified)
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

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The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective

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