Cited by 3,200Statistics Education and MethodologiesStatistical Methods in EpidemiologyMeta-analysis and systematic reviews

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Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations

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Greenland, Sander, Senn, Stephen J., Rothman, Kenneth J., Carlin, John B., Poole, Charles, Goodman, Steven N., Altman, Douglas G.·2016·European Journal of Epidemiology

DOI 10.1007/s10654-016-0149-3PMC PMC4877414

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Abstract

Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have been decried for decades, yet remain rampant. A key problem is that there are no interpretations of these concepts that are at once simple, intuitive, correct, and foolproof. Instead, correct use and interpretation of these statistics requires an attention to detail which seems to tax the patience of working scientists. This high cognitive demand has led to an epidemic of shortcut definitions and interpretations that are simply wrong, sometimes disastrously so-and yet these misinterpretations dominate much of the scientific literature. In light of this problem, we provide definitions and a discussion of basic statistics that are more general and critical than typically found in traditional introductory expositions. Our goal is to provide a resource for instructors, researchers, and consumers of statistics whose knowledge of statistical theory and technique may be limited but who wish to avoid and spot misinterpretations. We emphasize how violation of often unstated analysis protocols (such as selecting analyses for presentation based on the P values they produce) can lead to small P values even if the declared test hypothesis is correct, and can lead to large P values even if that hypothesis is incorrect. We then provide an explanatory list of 25 misinterpretations of P values, confidence intervals, and power. We conclude with guidelines for improving statistical interpretation and reporting.

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Authors: Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G.
Affiliations: University of California, Los Angeles (US)
Luxembourg Institute of Health (LU)
RTI International (US)
The University of Melbourne (AU)
University of North Carolina at Chapel Hill (US)
Stanford Medicine (US)
University of Oxford (GB)
Corresponding author: Greenland, Sander
ORCID: Greenland, Sander
Senn, Stephen J.
Rothman, Kenneth J.
Carlin, John B.
Poole, Charles
Goodman, Steven N.
Altman, Douglas G.
Venue: European Journal of Epidemiology
Publisher: Springer Science and Business Media LLC
Published: 2016-04
Volume: 31
Issue: 4
Pages: 337-350
ISSN: 0393-2990 (ISSN-L)
1573-7284
DOI: 10.1007/s10654-016-0149-3
PMC: PMC4877414
OpenAlex: W2408017125
Cited by: 3,200
References: 135
Citations by year: 2026: 325 · 2025: 454 · 2024: 407 · 2023: 290 · 2022: 348 · 2021: 392 · 2020: 330 · 2019: 270 · 2018: 201 · 2017: 148 · 2016: 33
FWCI: 220.87
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (unspecified)
Locations: European Journal of Epidemiology (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
eScholarship (California Digital Library) (submittedVersion, cc-by)
Minerva Access (University of Melbourne) (submittedVersion, cc-by)
Funders: Seventh Framework Programme (602552)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords: p-values, confidence intervals, statistical power, statistical misinterpretation, hypothesis testing, selective analysis, analysis protocol, statistical reporting guidelines, statistics education
MeSH terms: Data Interpretation, Statistical, Humans, Probability, Confidence Intervals

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