ArticleClinical trials (London, England)2020
Non-adjustment for multiple testing in multi-arm trials of distinct treatments: Rationale and justification.
Article in Clinical trials (London, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.
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Who cites it
41 citing papers in PubMed, 2 syntheses or guidelines pooled it.
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- Multiplicity adjustments in parallel-group multi-arm trials sharing a control group: Clear guidance is needed.Contemporary clinical trials · 2022Trial
- A Multi-Stage Drop-the-Loser Design With Superiority Boundaries.Statistics in medicine · 2026Article
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- Parenting in the Digital Era: Quantitative and Qualitative Insights from Families of Children with Neurodevelopmental Disorders.Children (Basel, Switzerland) · 2026Article
- Clinical Trial Simulation: Planning With the OCTAVE Framework, Implementation and Validation Principles.Statistics in medicine · 2026Article
- Parents' precarious work schedules and children's asthma management.BMC public health · 2026Article
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- Improving health behaviors and symptoms in youth with mental health disorders: The GamerFit RCT.Mental health and physical activity · 2025Article
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- An Epidemiologic Approach for Estimating Risk Reduction and Asymptotic Power on the Log-Difference Scale.International journal of environmental research and public health · 2025Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
There is currently a lack of consensus and uncertainty about whether one should adjust for multiple testing in multi-arm trials of distinct treatments. A detailed rationale is presented to justify non-adjustment in this situation. We argue that non-adjustment should be the default starting position in simple multi-arm trials of distinct treatments.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.