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

Dealing with multiplicities in pharmacoepidemiologic studies.

W F Rosenberger1

  • 1Department of Mathematics and Statistics, University of Maryland, Baltimore County, 5401 Wilkens Avenue, Baltimore, MD 21228-5398, USA.

Pharmacoepidemiology and Drug Safety
|March 1, 1996
PubMed
Summary

When testing multiple hypotheses in scientific research, adjusting significance levels is crucial. This ensures an accurate overall error rate, impacting study design and publication strategies.

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

A Bayesian Hybrid Adaptive Randomisation Design for Clinical Trials with Survival Outcomes.

Methods of information in medicine·2015
Same author

Association of fasting glucose with subclinical cerebrovascular disease in older adults without Type 2 diabetes.

Diabetic medicine : a journal of the British Diabetic Association·2013
Same author

Covariate-adjusted response-adaptive designs for binary response.

Journal of biopharmaceutical statistics·2002
Same author

Optimal adaptive designs for binary response trials.

Biometrics·2001
Same author

Analysis of time trends in adaptive designs with application to a neurophysiology experiment.

Statistics in medicine·2000
Same author

A comparison of urn designs for randomized clinical trials of K > 2 treatments.

Journal of biopharmaceutical statistics·2000

Area of Science:

  • Statistics
  • Scientific Methodology

Background:

  • The issue of multiplicity, or performing multiple statistical tests, is common in scientific research.
  • Uncorrected multiple testing inflates the overall Type I error rate, leading to false discoveries.

Purpose of the Study:

  • To explain the problem of multiplicity in scientific studies in an accessible manner.
  • To describe and motivate methods for addressing multiplicity.
  • To provide guidelines for study design and publication.

Main Methods:

  • Non-technical explanation of the statistical principles behind multiplicity.
  • Overview of common techniques for multiplicity adjustment.
  • Discussion of implications for research practices.

Main Results:

Related Experiment Videos

  • Understanding the necessity of adjusting significance levels when multiple hypotheses are tested.
  • Familiarity with various methods to control the overall error rate.
  • Awareness of how multiplicity affects study design and publication decisions.

Conclusions:

  • Properly addressing multiplicity is essential for maintaining the integrity of scientific findings.
  • Adherence to guidelines can improve the reliability of research outcomes.
  • Consideration of multiplicity should begin at the study design phase and extend through publication.