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

Optimal adaptive designs for binary response trials.

W F Rosenberger1, N Stallard, A Ivanova

  • 1Department of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore 21250, USA. billr@math.umbc.edu

Biometrics
|September 12, 2001
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

Precision Measurement of Neutrino Oscillation Parameters with 10 Years of Data from the NOvA Experiment.

Physical review letters·2026
Same author

Dual-Baseline Search for Active-to-Sterile Neutrino Oscillations in NOvA.

Physical review letters·2025
Same author

Studies on the significance of secretory IgA antibodies in the pathogenesis and clinical course of enterobiasis in infected persons from Bulgaria: preliminary findings.

Helminthologia·2025
Same author

Search for CP-Violating Neutrino Nonstandard Interactions with the NOvA Experiment.

Physical review letters·2024
Same author

INFLAMMATORY FACTORS IN DISSECTION OF THORACIC AORTIC ANEURYSM.

Georgian medical news·2024
Same author

Comparison of Preimplantation Mouse Embryos with Different Genetic Backgrounds as Models for Evaluating Human Embryo Culture Media Composition.

Reproductive sciences (Thousand Oaks, Calif.)·2024
Same journal

Fast penalized generalized estimating equations for large longitudinal functional datasets.

Biometrics·2026
Same journal

Causally-interpretable random-effects meta-analysis.

Biometrics·2026
Same journal

Statistical inference for mean function of partially observed functional time series.

Biometrics·2026
Same journal

Subgroup identification via Interaction Tree and Mixed Model for Repeated Measures with application to Alzheimer's disease.

Biometrics·2026
Same journal

Finite mixtures of linear quantile regressions with concomitant variables: a solution to endogeneity in longitudinal data modeling.

Biometrics·2026
Same journal

Discussion on "INTACT: a method for integration of longitudinal physical activity data from multiple sources" by Jingru Zhang, Erjia Cui, Hongzhe Li, and Haochang Shou.

Biometrics·2026
See all related articles

This study introduces an optimal clinical trial design to minimize treatment failures. The proposed sequential method generally reduces failures compared to other allocation strategies, especially with lower treatment success rates.

Area of Science:

  • Clinical Trials
  • Biostatistics
  • Medical Research

Background:

  • Optimizing treatment allocation in clinical trials is crucial for patient outcomes.
  • Minimizing treatment failures while maintaining statistical power is a key challenge.
  • Existing allocation methods may not be efficient, particularly in early-phase trials or when treatment efficacy varies.

Purpose of the Study:

  • To derive the optimal allocation strategy for two treatments in a clinical trial.
  • To minimize the expected number of treatment failures for a fixed variance of the test statistic.
  • To introduce and evaluate a sequential design that asymptotically achieves this optimal allocation.

Main Methods:

  • Derivation of an optimal allocation criterion based on minimizing expected treatment failures.

Related Experiment Videos

  • Development of a sequential clinical trial design.
  • Asymptotic comparison of the proposed sequential design with existing methods: randomized play-the-winner, sequential Neyman allocation, and equal allocation.
  • Evaluation of performance at similar power levels.

    • Main Results:

    • The derived optimal allocation minimizes expected treatment failures for a fixed test statistic variance.
    • The proposed sequential design asymptotically approaches this optimal allocation.
    • The sequential procedure demonstrated fewer treatment failures compared to randomized play-the-winner, sequential Neyman, and equal allocation.
    • This advantage was particularly pronounced when the success probabilities of the treatments were smaller.

    Conclusions:

    • The novel sequential allocation design is superior in minimizing treatment failures in clinical trials.
    • This design offers significant benefits, especially in scenarios with lower treatment success probabilities.
    • The findings provide a more efficient approach to clinical trial design, potentially improving patient outcomes and resource utilization.