An introduction to multiplicity issues in clinical trials: the what, why, when and how
Open accessAbstract
In clinical trials it is not uncommon to face a multiple testing problem which can have an impact on both type I and type II error rates, leading to inappropriate interpretation of trial results. Multiplicity issues may need to be considered at the design, analysis and interpretation stages of a trial. The proportion of trial reports not adequately correcting for multiple testing remains substantial. The purpose of this article is to provide an introduction to multiple testing issues in clinical trials, and to reduce confusion around the need for multiplicity adjustments. We use a tutorial, question-and-answer approach to address the key issues of why, when and how to consider multiplicity adjustments in trials. We summarize the relevant circumstances under which multiplicity adjustments ought to be considered, as well as options for carrying out multiplicity adjustments in terms of trial design factors including Population, Intervention/Comparison, Outcome, Time frame and Analysis (PICOTA). Results are presented in an easy-to-use table and flow diagrams. Confusion about multiplicity issues can be reduced or avoided by considering the potential impact of multiplicity on type I and II errors and, if necessary pre-specifying statistical approaches to either avoid or adjust for multiplicity in the trial protocol or analysis plan.
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The best methods for taking multiple outcomes into account are debated.
“It is worth noting that the best methods for taking multiple outcomes into account are debated.31”
When multiple comparisons are performed, the risk of false positives (type 1 error) is inflated.
“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 [411]
Trials are often affected by multiplicity issues.
“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 [411]
No standardised rules exist for dealing with multiplicity.
“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 [411]
Guidance is available on key problems to consider for dealing with multiplicity.
“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 [411]
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- Authors
- Li, G., Taljaard, M., Van den Heuvel, E. R., Levine, M. A., Cook, D. J., Wells, G. A., Devereaux, P. J., & Thabane, L.
- Affiliations
- St. Joseph’s Healthcare Hamilton (CA)
- University of Ottawa (CA)
- Population Health Research Institute (CA)
- Corresponding author
- Li, Guowei
- ORCID
- Venue
- International Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-12-26
- Volume
- 46
- Issue
- 2
- Pages
- dyw320
- ISSN
- 0300-5771 (ISSN-L)
- 1464-3685
- OpenAlex
- W2567636536
- Cited by
- 381
- References
- 64
- Citations by year
- 2026: 31 · 2025: 47 · 2024: 55 · 2023: 46 · 2022: 41 · 2021: 61 · 2020: 61 · 2019: 28 · 2018: 7 · 2017: 4
- FWCI
- 13.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- TU/e Research Portal (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- TU/e Research Portal (submittedVersion, other-oa)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- multiplicity adjustment, multiple comparisons, clinical trials, type I error, type II error, trial design, statistical analysis plan, Picota, trial reporting
- MeSH terms
- Data Interpretation, Statistical, Humans, Research Design, Confidence Intervals, Randomized Controlled Trials as Topic
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