Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Protocol designed subgroup analyses in multiarmed clinical trials: multiplicity aspects.

Egbert H E Biesheuvel1, Ludwig A Hothorn

  • 1Biometrics Department, NV Organon, Oss, The Netherlands. egbert.biesheuvel@organon.com

Journal of Biopharmaceutical Statistics
|October 31, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Plant Kelch phosphatases are Ser/Thr phosphatases involved in cell cycle regulation.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

The role of statistical power in context: implications for regulatory practices.

Integrated environmental assessment and management·2026
Same author

Multiple Contrast Tests for Count Data: Small Sample Approximations and Their Limitations.

Biometrical journal. Biometrische Zeitschrift·2025
Same author

Analysis of Covariance in General Factorial Designs Through Multiple Contrast Tests Under Variance Heteroscedasticity.

Statistics in medicine·2025
Same author

Multiple Contrast Tests in the Presence of Partial Heteroskedasticity.

Biometrical journal. Biometrische Zeitschrift·2025
Same author

Simultaneous Inference Using Multiple Marginal Models.

Pharmaceutical statistics·2024

Subgroup analyses in clinical trials often lack adjustments for multiple testing, increasing false positives. This paper addresses multiplicity in subgroup analyses for multiarmed trials, offering practical guidance.

Area of Science:

  • Clinical Trials Methodology
  • Biostatistics
  • Statistical Inference

Background:

  • Subgroup analyses are frequently performed in clinical trials to explore treatment effects in specific patient populations.
  • Unadjusted subgroup findings can lead to an inflated risk of false positive results due to multiple comparisons.
  • Lack of standardized approaches for multiplicity adjustment in subgroup analyses poses challenges for interpretation.

Purpose of the Study:

  • To examine the multiplicity issues inherent in subgroup analyses within multiarmed randomized clinical trials.
  • To provide practical recommendations for addressing the statistical challenges of subgroup analyses.
  • To enhance the reliability and interpretability of subgroup findings in clinical research.

Main Methods:

Related Experiment Videos

  • Focuses on the statistical principles of multiplicity in the context of subgroup analyses.
  • Discusses the implications of unadjusted comparisons in multiarmed trials.
  • Reviews common practices and their statistical consequences.

    • Main Results:

    • Unadjusted subgroup analyses significantly increase the probability of false positive findings.
    • The multiplicity of subgroup analyses is a critical factor often overlooked in reporting.
    • Guidance is provided to mitigate the risks associated with multiple testing in subgroup investigations.

    Conclusions:

    • Adjusting for multiplicity in subgroup analyses is crucial for accurate clinical trial interpretation.
    • Practitioners should be aware of and implement methods to control false positive rates in subgroup findings.
    • Adopting rigorous statistical approaches enhances the validity of subgroup conclusions in multiarmed trials.