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 Concept Videos

Randomized Experiments01:13

Randomized Experiments

8.6K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
8.6K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

399
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
399
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

82
Body:Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to...
82
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

258
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
258
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

70
Body:Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
70
Blinding01:11

Blinding

3.7K
Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.
3.7K

You might also read

Related Articles

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

Sort by
Same author

Generalized Pairwise Comparisons in Dose Optimization Oncology Trials: Beyond Safety to Multi-outcome Dose Selection.

Clinical cancer research : an official journal of the American Association for Cancer Research·2026
Same author

International Consensus-Driven Recommendations for Patient-Reported Outcome Research Objectives in Early Phase Dose-Finding Oncology Trials: OPTIMISE-ROR.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology·2026
Same author

Nous-209 neoantigen vaccine for cancer prevention in Lynch syndrome carriers: a phase 1b/2 trial.

Nature medicine·2026
Same author

Investigation of Profile-Related Evidence Determining Individualized Cancer Therapy (I-PREDICT) N-of-1 Precision Oncology Study: Molecular Profiling to Match Individually Dosed, Personalized Drug Combinations.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology·2026
Same author

MET Overexpression Is Associated with Superior Immunotherapy Benefit in Advanced Non-Small Cell Lung Cancer.

Cancers·2025
Same author

Chemotherapy alone for stage II-IVa laryngeal squamous cell carcinoma: A 20-year follow-up.

Cancer·2025
Same journal

Regression analysis of misclassified current status data with potentially unknown test accuracy.

Statistical methods in medical research·2026
Same journal

Bayesian multivariate linear mixed-effects models with varied association structures.

Statistical methods in medical research·2026
Same journal

Inference about the ratio of age-standardized rates between two overlapping populations.

Statistical methods in medical research·2026
Same journal

A robust neural network with random effects for subject-specific prediction of clustered count data.

Statistical methods in medical research·2026
Same journal

A comparison of methods for designing hybrid type 2 cluster-randomized trials with continuous effectiveness and implementation endpoints.

Statistical methods in medical research·2026
Same journal

Joint analysis of longitudinal and recurrent event data: A functional regression approach with autoregressive frailty.

Statistical methods in medical research·2026
See all related articles

Related Experiment Video

Updated: Nov 14, 2025

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

881

Evaluating Bayesian adaptive randomization procedures with adaptive clip methods for multi-arm trials.

Kim May Lee1, J Jack Lee2

  • 1MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.

Statistical Methods in Medical Research
|March 10, 2021
PubMed
Summary
This summary is machine-generated.

Bayesian adaptive randomization can now be improved with an adaptive clip method, reducing patient assignment to inferior treatment arms. A new utility approach aids in selecting the best randomization strategy for clinical trials.

Keywords:
Adaptive clip methodadaptive randomizationmulti-arm trialspatient horizonutility

More Related Videos

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.3K

Related Experiment Videos

Last Updated: Nov 14, 2025

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

881
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.3K

Area of Science:

  • Clinical Trials
  • Biostatistics
  • Medical Research

Background:

  • Bayesian adaptive randomization is a clinical trial strategy that allocates more patients to better-performing treatment arms based on emerging data.
  • Existing methods have limitations, including the risk of assigning patients to suboptimal treatments, raising concerns for real-world applications.
  • Limited research focuses on enhancing the performance and practical application of Bayesian adaptive randomization in clinical trials.

Purpose of the Study:

  • To introduce an adaptive clip method to improve Bayesian adaptive randomization by minimizing early-stage assignment to inferior arms.
  • To propose a utility-based approach for selecting optimal randomization procedures in clinical trials.
  • To provide a framework for selecting randomization strategies considering patient benefit and the cost of assigning patients to inferior arms.

Main Methods:

  • Developed an adaptive clip method incorporating a data-driven function to modify Bayesian adaptive randomization.
  • Introduced a utility function that quantifies the penalty for assigning patients to inferior arms and the overall patient benefit.
  • Illustrated a strategy for selecting the most appropriate randomization procedure across various clinical trial scenarios.

Main Results:

  • The adaptive clip method effectively reduces the probability of assigning patients to inferior treatment arms, particularly in the early phases of a trial.
  • The proposed utility approach provides a quantitative basis for selecting randomization procedures, balancing treatment efficacy and ethical considerations.
  • Demonstrated the applicability of the selection strategy through diverse simulated clinical trial scenarios.

Conclusions:

  • The adaptive clip method offers a significant improvement over standard Bayesian adaptive randomization, enhancing patient safety and trial efficiency.
  • The utility approach facilitates informed decision-making in selecting adaptive randomization strategies, crucial for optimizing clinical trial design.
  • These advancements provide practical guidance for implementing more robust and ethical adaptive randomization in clinical practice.