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

Evaluating subject-treatment interaction when comparing two treatments.

G L Gadbury1, H K Iyer, D B Allison

  • 1Department of Mathematics and Statistics, Univesity of Missouri-Rolla, 65409, USA. gadburyg@umr.edu

Journal of Biopharmaceutical Statistics
|May 23, 2002
PubMed
Summary

Average treatment effects can mislead when individual patient responses vary. This study introduces methods to evaluate subject-treatment interaction, revealing when a portion of the population may not benefit from a treatment.

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

Letter to the editor: Insufficient Reporting of Randomization Procedures and Unexplained Unequal Allocation: A Commentary on "Dairy-Based and Energy-Enriched Berry-Based Snacks Improve or Maintain Nutritional and Functional Status in Older People in Home Care.

The journal of nutrition, health & aging·2019
Same author

The stated conclusions are contradicted by the data, based on inappropriate statistics, and should be corrected: comment on 'intervention for childhood obesity based on parents only or parents and child compared with follow-up alone'.

Pediatric obesity·2018
Same author

GWAS for BMI: a treasure trove of fundamental insights into the genetic basis of obesity.

International journal of obesity (2005)·2018
Same author

Regression to the mean, apparent data errors and biologically extraordinary results: letter regarding 'changes in telomere length 3-5 years after gastric bypass surgery'.

International journal of obesity (2005)·2017
Same author

Generalized lambda distribution for flexibly testing differences beyond the mean in the distribution of a dependent variable such as body mass index.

International journal of obesity (2005)·2017
Same author

Social status and energy intake: a randomized controlled experiment.

Clinical obesity·2017

Area of Science:

  • Biostatistics
  • Clinical Trial Methodology
  • Pharmacogenetics

Background:

  • Mean treatment effects can obscure significant individual variability in treatment response.
  • Understanding subject-treatment interaction is crucial for accurate clinical trial interpretation.

Purpose of the Study:

  • To develop and present methods for evaluating individual treatment heterogeneity (subject-treatment interaction).
  • To assess the consequences of such heterogeneity in clinical experiments.
  • To provide tools for practitioners to identify and understand variations in treatment effects.

Main Methods:

  • Utilized maximum likelihood estimation to derive estimators for subject-treatment interaction.
  • Presented a bootstrap procedure as a less assumption-dependent alternative for small samples.

Related Experiment Videos

  • Illustrated sensitivity of estimators to an inestimable correlation parameter using data and plots.

    • Main Results:

    • Subject-treatment interaction indicates that some individuals may not respond to treatment despite a positive average effect.
    • Estimators for subject-treatment interaction are sensitive to an inestimable correlation parameter.
    • Graphical plots and example datasets demonstrate this sensitivity.

    Conclusions:

    • Proposed methods can alert clinicians to widespread individual treatment effect variation.
    • These methods aid in assessing the potential consequences of treatment heterogeneity.
    • Findings are applicable to clinical decision-making, pharmacogenetics, and other research areas.