Cited by 2,046Statistical Methods and Bayesian InferenceStatistical Methods in Clinical TrialsStatistical Methods in Epidemiology

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The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis

Hoenig, John M, Heisey, Dennis M·2001·The American Statistician

DOI 10.1198/000313001300339897

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Abstract

It is well known that statistical power calculations can be valuable in planning an experiment. There is also a large literature advocating that power calculations be made whenever one performs a statistical test of a hypothesis and one obtains a statistically nonsignificant result. Advocates of such post-experiment power calculations claim the calculations should be used to aid in the interpretation of the experimental results. This approach, which appears in various forms, is fundamentally flawed. We document that the problem is extensive and present arguments to demonstrate the flaw in the logic.

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“Though post-hoc power calculations are discouraged (Hoenig and Heisey, 2001), we can assume that our sample (six studies, on average 200 participants per condition) approached sufficient size to detect the effect of g = 0.26.”
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Authors: Hoenig, J. M., & Heisey, D. M.
Affiliations: University of Wisconsin–Madison (US)
ORCID: Hoenig, John M
Venue: The American Statistician
Publisher: Informa UK Limited
Published: 2001-02
Volume: 55
Issue: 1
Pages: 19-24
ISSN: 0003-1305 (ISSN-L)
1537-2731
DOI: 10.1198/000313001300339897
OpenAlex: W2069523442
Cited by: 2,046
References: 38
Citations by year: 2026: 213 · 2025: 104 · 2024: 80 · 2023: 97 · 2022: 111 · 2021: 111 · 2020: 124 · 2019: 131 · 2018: 103 · 2017: 87 · 2016: 90 · 2015: 79 · 2014: 84 · 2013: 89 · 2012: 79
FWCI: 42.63
Type: journal article
Language: en
Open access: closed
Locations: The American Statistician (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords: statistical power, non-significant results, experimental design

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The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis

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