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

Bioavailability Study Design: Single Versus Multiple Dose Studies01:11

Bioavailability Study Design: Single Versus Multiple Dose Studies

Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
Crossover Experiments01:16

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
Bioequivalence of Drugs: Drugs with Multiple Indications01:09

Bioequivalence of Drugs: Drugs with Multiple Indications

The concept of therapeutic equivalence (TE) in drugs with multiple indications is complex. A generic drug may be therapeutically equivalent to a brand-name product for one specific indication, but this doesn't necessarily mean it's equivalent for all other indications. Evidence of TE in one patient group and bioequivalence shown in healthy volunteers can support—but not confirm—TE for other indications. However, definitive proof requires individual clinical studies for each indication due to...
Multiple Comparison Tests01:13

Multiple Comparison Tests

Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
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

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...
Clinical Trials: Overview01:11

Clinical Trials: Overview

Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...

You might also read

Related Articles

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

Sort by
Same author

Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift.

Proceedings of machine learning research·2026
Same author

Deep learning-enabled temporal sequencing of metasurface for rewritable and customizable electromagnetic illusions.

National science review·2026
Same author

Study on the driving mechanisms of land use change on water yield and carbon storage based on the InVEST-PLUS-GeoDetector model.

Scientific reports·2026
Same author

Borrowing information from an unidentifiable model: Guaranteed efficiency gain with a dichotomized outcome in the external data.

Biometrics·2026
Same author

LL-37 Inhibits EV71 Infection by Upregulating STAC via the EGFR-ERK Signaling Pathway.

Viruses·2026
Same author

Nonlinear variation of discharge coefficient and energy dissipation optimization for bottom outlet of EG reservoir: an integral hydraulic model study.

Scientific reports·2026
Same journal

Interpretable Bayesian Modeling for Multireader Multicase Studies: Addressing Overdispersion and Limited Sample Size in Diagnostic Enhancement Evaluation.

Statistics in medicine·2026
Same journal

Adaptive Sequential Multiple Hypotheses Testing for Concomitant Vaccine Safety Surveillance.

Statistics in medicine·2026
Same journal

Novel Distance Regression for Repeated Outcomes With Missing Data: Applications to Longitudinal and Crossover Studies of Microbiome Beta-Diversity.

Statistics in medicine·2026
Same journal

Optimal Weighted Tests for Replication Studies and the 'Two-Trials Rule' With Multiple Hypotheses.

Statistics in medicine·2026
Same journal

Identifiable Copula-Double-Cox Models: A Fully Parametric Framework for Dependent Right-Censored Survival Data.

Statistics in medicine·2026
Same journal

Moving From Individualized Risk-Based Prevention to Benefit-Based Prevention: Estimating Individualized Life-Years Gained From Prevention Services as a Basis for Eligibility.

Statistics in medicine·2026
See all related articles

Related Experiment Video

Updated: May 22, 2026

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations
11:15

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations

Published on: July 24, 2021

Multiple testing for a combination drug with two study endpoints.

Jun Shao1, Sheng Zhang, Jiwei Zhao

  • 1School of Finance and Statistics, East China Normal University, Shanghai 200241, China. shao@stat.wisc.edu

Statistics in Medicine
|May 12, 2012
PubMed
Summary
This summary is machine-generated.

New multiple testing procedures using bootstrap methods can identify superior combination drugs more effectively than traditional methods. These advanced techniques improve the analysis of combination drug trials, especially with multiple study endpoints.

More Related Videos

Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation
15:04

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation

Published on: January 19, 2019

Related Experiment Videos

Last Updated: May 22, 2026

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations
11:15

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations

Published on: July 24, 2021

Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation
15:04

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation

Published on: January 19, 2019

Area of Science:

  • Biostatistics
  • Pharmacology
  • Clinical Trial Design

Background:

  • Combination drug products with multiple active compounds offer potential advantages in efficacy, cost, and safety over individual components.
  • Factorial designs are commonly used in clinical trials to evaluate various dose combinations of drug components.
  • Existing multiple testing procedures, like Holm's step-down, can be overly conservative, potentially missing significant findings.

Purpose of the Study:

  • To develop and evaluate novel bootstrap-based multiple testing procedures for identifying superior combination drug therapies.
  • To enhance the power of statistical tests in clinical trials involving combination drugs with multiple dose levels.
  • To address the complexities of applying bootstrap methods in studies with multiple study endpoints.

Main Methods:

  • Utilized bootstrap methods to construct multiple testing procedures for simultaneously identifying superior drug combinations.
  • Employed an upper bound strategy to control the familywise error rate in the presence of multiple endpoints.
  • Compared the power of the proposed bootstrap procedures against Holm's step-down procedure in simulation studies.

Main Results:

  • The developed bootstrap multiple testing procedures demonstrated greater statistical power compared to Holm's procedure.
  • The methods successfully identified superior drug combinations across various dose levels.
  • The proposed approach provides a viable solution for analyzing combination drug trials with multiple endpoints.

Conclusions:

  • Bootstrap-based multiple testing procedures offer a more powerful alternative for analyzing combination drug trials.
  • These methods are particularly beneficial for studies with multiple endpoints, improving the identification of effective drug combinations.
  • The findings support the application of these advanced statistical techniques in pharmaceutical research and development.