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

8.8K
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...
8.8K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

360
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
360
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

226
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...
226
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

179
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...
179
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

406
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,...
406
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

881
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
881

You might also read

Related Articles

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

Sort by
Same author

Safety-Driven Response Adaptive Randomization: An Application in Noninferiority Oncology Trials.

Statistics in medicine·2026
Same author

Sotatercept reduces bone morphogenetic protein signaling in patients with pulmonary arterial hypertension.

Science translational medicine·2026
Same author

A burn-in(g) question: How long should an initial equal randomization stage be before Bayesian response-adaptive randomization?

Statistical methods in medical research·2026
Same author

Endoglin as a BMP9 co-receptor in vascular endothelial cells: prodomain displacement and TGFBRII recruitment.

Nature communications·2025
Same author

BMP9 knockout impairs pulmonary vessel muscularisation and confers aberrant tamoxifen sensitivity.

Angiogenesis·2025
Same author

Drug Development for Pulmonary Arterial Hypertension: Unleashing the Potential of Single-Patient Studies Using Continuous Monitoring.

Pulmonary circulation·2025
Same journal

A joint model for a longitudinal outcome and a progressive multistate model under a mixed observation scheme.

Statistical methods in medical research·2026
Same journal

Efficient semi-supervised estimation of optimal individualized treatment regimes with survival outcome.

Statistical methods in medical research·2026
Same journal

Asymptotic online FWER control for dependent test statistics.

Statistical methods in medical research·2026
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
See all related articles

Related Experiment Video

Updated: Jan 15, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

15.0K

Implementing response-adaptive randomisation in stratified rare-disease trials: Design challenges and practical

Rajenki Das1, Nina Deliu1,2, Mark R Toshner3,4

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

Statistical Methods in Medical Research
|October 6, 2025
PubMed
Summary
This summary is machine-generated.

Response-adaptive randomization (RAR) in clinical trials faces practical challenges. This study introduces a Mapping strategy for better allocation in small samples and addresses missing data impacts during interim analyses.

Keywords:
Adaptive designsadaptive randomisationimplementationmappingrare disease

More Related Videos

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

602
Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
08:46

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms

Published on: December 9, 2015

11.1K

Related Experiment Videos

Last Updated: Jan 15, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

15.0K
Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

602
Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
08:46

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms

Published on: December 9, 2015

11.1K

Area of Science:

  • Clinical Trials Methodology
  • Biostatistics
  • Rare Disease Research

Background:

  • Response-adaptive randomization (RAR) is underutilized in clinical trials despite its potential.
  • Practical implementation challenges, especially in small sample sizes and rare diseases, are often overlooked.
  • Existing technical literature frequently neglects real-world trial complexities.

Purpose of the Study:

  • To address practical challenges in implementing response-adaptive randomization (RAR) in clinical trials.
  • To ensure RAR allocations are both acceptable and statistically faithful, particularly in small sample sizes.
  • To determine appropriate adaptations following interim analyses when dealing with missing data.

Main Methods:

  • Proposed a 'Mapping' strategy to discretize randomization probabilities into allocation ratios for improved frequentist errors.
  • Analyzed the impact of missing data on operating characteristics under the Mapping strategy.
  • Investigated practical considerations such as data pooling, blinding assessment, and safety reporting.

Main Results:

  • The Mapping strategy enhances the desirability of RAR allocations, ensuring they are acceptable and faithful to intended probabilities, especially in small samples.
  • Missing data can significantly impact operating characteristics, necessitating careful consideration during interim analyses.
  • The study provides a framework for addressing practical RAR implementation issues.

Conclusions:

  • The Mapping strategy offers a viable solution for improving RAR implementation in small and rare disease trials.
  • Addressing missing data is crucial for successful adaptive trial designs.
  • Further research and discussion on practical aspects like blinding and safety reporting are warranted for wider RAR adoption.