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

More powerful procedures for multiple significance testing.

Y Hochberg1, Y Benjamini

  • 1Department of Statistics, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Israel.

Statistics in Medicine
|July 1, 1990
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

TreeQTL: hierarchical error control for eQTL findings.

Bioinformatics (Oxford, England)·2016
Same author

Selective correlations; not voodoo.

NeuroImage·2014
Same author

Revisiting multi-subject random effects in fMRI: advocating prevalence estimation.

NeuroImage·2013
Same author

Non-linear formulas for the spinal cord injury ability realization measurement index.

Spinal cord·2011
Same author

A new grading for easy and concise description of functional status after spinal cord lesions.

Spinal cord·2011
Same author

Estimating wall guidance and attraction in mouse free locomotor behavior.

Genes, brain, and behavior·2007
Same journal

A Causal Framework for Evaluating the Total Effect of Strategies Aiming to Expand Screening and to Improve Outcomes.

Statistics in medicine·2026
Same journal

Causal Effects on Nonterminal Event Time With Application to Antibiotic Usage and Future Resistance.

Statistics in medicine·2026
Same journal

Subgroup Analysis of Interval-censored Failure Time Data With Application to Alzheimer's Disease.

Statistics in medicine·2026
Same journal

Rejoinder to Commentaries on "A Perspective on the Appropriate Implementation of ICH E9(R1) Addendum Strategies for Handling Intercurrent Events".

Statistics in medicine·2026
Same journal

A Multi-Stage Drop-the-Loser Design With Superiority Boundaries.

Statistics in medicine·2026
Same journal

Interpretable ROI Identification in Brain Image Analysis: Overcoming CNN Black Box Challenges With Kriging-Enhanced Adaptive Sampling.

Statistics in medicine·2026
See all related articles

This study introduces new, powerful methods to address the challenge of multiple comparisons in medical research. These advanced statistical procedures offer improved analysis for complex health studies.

Area of Science:

  • Medical Statistics
  • Biostatistics
  • Health Research Methodology

Background:

  • The issue of multiple comparisons poses a significant challenge in medical research, potentially leading to false discoveries.
  • Classical multiple comparison procedures often lack the statistical power needed for complex datasets.

Purpose of the Study:

  • To introduce novel, general, and user-friendly statistical procedures for handling multiple comparisons in medical research.
  • To demonstrate the utility of these new methods using real-world medical data.

Main Methods:

  • Development and description of new, broadly applicable statistical methods for multiple comparisons.
  • Application of these methods to two distinct medical research examples.

Main Results:

Related Experiment Videos

  • The proposed procedures offer enhanced statistical power compared to traditional methods.
  • Demonstrated successful application in analyzing neuropsychological effects of lead exposure and sleep patterns in alcoholics.

Conclusions:

  • The new statistical procedures are effective and practical for addressing multiple comparison issues in medical research.
  • These methods can improve the reliability and validity of findings in complex health studies.