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Multiplicity Considerations in Clinical Trials
Abstract
Making multiple comparisons increases the likelihood that a chance association could be interpreted as causal. A number of statistical approaches can facilitate the precise interpretation of clinical trial results.
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“When multiple comparisons are performed (eg, multiple outcomes, time points, subpopulations, interim analyses), the risk of false positives (type 1 error) is inflated.”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [412]
In the citing paper
“Trials are often affected by multiplicity issues.411 412”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [412]
In the citing paper
“Although no standardised rules exist for dealing with multiplicity, guidance is available on key problems to consider.411 412”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [412]
In the citing paper
“Although no standardised rules exist for dealing with multiplicity, guidance is available on key problems to consider.411 412”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [412]
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Metadata
- Authors
- Dmitrienko, A., & D’Agostino, R. B.
- Affiliations
- Boston University (US)
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2018-05-31
- Volume
- 378
- Issue
- 22
- Pages
- 2115-2122
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2806596191
- Cited by
- 140
- References
- 30
- Citations by year
- 2026: 14 · 2025: 18 · 2024: 16 · 2023: 6 · 2022: 22 · 2021: 22 · 2020: 19 · 2019: 16 · 2018: 7
- FWCI
- 2.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- multiplicity, multiple comparisons, clinical trials, statistical significance, false positives, causal inference
- MeSH terms
- Data Interpretation, Statistical, Humans, Research Design, Statistics as Topic, Causality, Clinical Trials, Phase III as Topic
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