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

Simple solution to a common statistical problem: interpreting multiple tests.

Toufigh Gordi1, Harry Khamis

  • 1Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy, Uppsala University, Uppsala, Sweden.

Clinical Therapeutics
|June 29, 2004
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

Parents' Report of Their Children's Underinsurance Status After the Affordable Care Act.

Journal of the American Board of Family Medicine : JABFM·2021
Same author

Integrated population pharmacokinetics of etirinotecan pegol and its four metabolites in cancer patients with solid tumors.

Cancer chemotherapy and pharmacology·2018
Same author

Population Pharmacokinetics of Boosted-Elvitegravir in HIV-Infected Patients.

Journal of clinical pharmacology·2015
Same author

Pharmacokinetic analysis of 14C-ursodiol in newborn infants using accelerator mass spectrometry.

Journal of clinical pharmacology·2014
Same author

Parents' perspectives on their children's health insurance: plight of the underinsured.

The Journal of pediatrics·2012
Same author

Steady-state pharmacokinetics of gabapentin after administration of a novel gastroretentive extended-release formulation in postmenopausal women with vasomotor symptoms.

Clinical drug investigation·2012

Researchers often misinterpret multiple statistical tests, leading to false positives. The Bonferroni test helps control this by ensuring statistical significance claims are valid, even with many tests.

Area of Science:

  • Statistics
  • Scientific methodology

Background:

  • Misinterpretation of multiple statistical tests is common in scientific literature.
  • Researchers often incorrectly declare significance for individual tests (P < 0.05) without accounting for multiple comparisons.
  • This practice inflates the risk of false-positive results, as the probability of Type I errors increases with the number of tests performed.

Purpose of the Study:

  • To raise awareness and understanding of the sequentially rejective Bonferroni test.
  • To encourage the wider adoption of this statistical method in research.

Main Methods:

  • The article explains the statistical problem arising from multiple comparisons.
  • It demonstrates how the sequentially rejective Bonferroni test controls the overall Type I error rate.

Related Experiment Videos

  • The method ensures that the probability of incorrectly declaring one or more significant results is bounded (e.g., at 0.05).

    • Main Results:

    • The sequentially rejective Bonferroni test provides a robust solution to the problem of multiple comparisons.
    • Its application bounds the overall Type I error rate, preventing inflated false-positive claims.

    Conclusions:

    • The sequentially rejective Bonferroni test is a practical and adaptable statistical tool.
    • It allows researchers to conduct simultaneous statistical inferences reliably, maintaining a controlled overall Type I error rate.