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

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...
Principle of Equivalence01:18

Principle of Equivalence

According to Albert Einstein (1897-1955), free-falling and feeling weightless are intrinsically linked. If a person were in free-fall under gravity, for example, diving towards the Earth from an airplane, they would feel completely weightless. Similarly, a person descending in a lift may feel partially weightless. Broadly speaking, it is assumed that an object in a uniform gravitational field and an object undergoing constant acceleration in the absence of gravity are under the same...
Second Uniqueness Theorem01:16

Second Uniqueness Theorem

Consider a region consisting of several individual conductors with a definite charge density in the region between these conductors. The second uniqueness theorem states that if the total charge on each conductor and the charge density in the in-between region are known, then the electric field can be uniquely determined.
In contrast, consider that the electric field is non-unique and apply Gauss's law in divergence form in the region between the conductors and the integral form to the surface...
Comparison Tests01:28

Comparison Tests

An infinite series composed of positive terms may either approach a finite value or increase without bound. Determining which outcome occurs is a central task in calculus, and comparison tests provide structured methods for making this determination. Rather than evaluating a series directly, these tests relate it to another series whose behavior is already known, allowing conclusions to be drawn through logical comparison.The direct comparison test applies to series with positive terms. If each...
Test for Homogeneity01:23

Test for Homogeneity

The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can be stated as...
Bonferroni Test01:10

Bonferroni Test

The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...

You might also read

Related Articles

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

Sort by
Same author

NeMO Analytics: a compendium of transcriptomic data for the exploration of neocortical development.

Nature neuroscience·2026
Same author

GAMing the Brain: Investigating the Cross-modal Relationships between Functional Connectivity and Structural Features using Generalized Additive Models.

Machine learning in clinical neuroimaging : 7th international workshop, MLCN 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, proceedings. MLCN (Workshop) (7th : 2024 : Marrakesh, Morocco)·2026
Same author

Corrigendum to 'Brief parent-report measure of slowness in eating is associated with weight status in children with cystic fibrosis over a 3-year follow-up', Physiology & Behavior 2025 115104.

Physiology & behavior·2026
Same author

Shortcomings of deep learning for distributional predictors: a note.

Biostatistics (Oxford, England)·2026
Same author

Baseline Functional Connectivity Predicts Who Will Benefit From Neuromodulation: Evidence From Primary Progressive Aphasia.

Neurorehabilitation and neural repair·2026
Same author

Brief parent-report measure of slowness in eating is associated with weight status in children with cystic fibrosis over a 3-year follow-up.

Physiology & behavior·2025
Same journal

Conceptualizing Experimental Controls Using the Potential Outcomes Framework.

The American statistician·2025
Same journal

A Cornucopia of Maximum Likelihood Algorithms.

The American statistician·2025
Same journal

A Multiple Imputation Approach for the Cumulative Incidence, with Implications for Variance Estimation.

The American statistician·2025
Same journal

An Example to Illustrate Randomized Trial Estimands and Estimators.

The American statistician·2025
Same journal

Laplace's law of succession estimator and M-statistics.

The American statistician·2025
Same journal

Counternull sets in randomized experiments.

The American statistician·2025
See all related articles

Related Experiment Video

Updated: Jun 17, 2026

One Dimensional Turing-Like Handshake Test for Motor Intelligence
14:05

One Dimensional Turing-Like Handshake Test for Motor Intelligence

Published on: December 15, 2010

Easy Multiplicity Control in Equivalence Testing Using Two One-sided Tests.

Carolyn Lauzon1, Brian Caffo

  • 1Department of Biophysics and Department of Biostatistics, Johns Hopkins University.

The American Statistician
|January 5, 2010
PubMed
Summary
This summary is machine-generated.

Equivalence testing using two one-sided tests (TOST) can inflate error rates with multiple comparisons. Scaling the Type I error rate by (k-1) controls the family-wise error rate effectively and less conservatively than Bonferroni correction.

More Related Videos

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

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology
10:52

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology

Published on: April 23, 2019

Related Experiment Videos

Last Updated: Jun 17, 2026

One Dimensional Turing-Like Handshake Test for Motor Intelligence
14:05

One Dimensional Turing-Like Handshake Test for Motor Intelligence

Published on: December 15, 2010

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

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology
10:52

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology

Published on: April 23, 2019

Area of Science:

  • Statistics
  • Biostatistics
  • Scientific Methodology

Background:

  • Equivalence testing is increasingly used in scientific research beyond drug approval.
  • The two one-sided tests (TOST) procedure is the most common method for equivalence testing.
  • TOST, like traditional hypothesis testing, faces multiplicity issues with multiple comparisons.

Purpose of the Study:

  • To address family-wise error rate concerns in equivalence testing with multiple comparisons.
  • To provide a condition for bounding the family-wise error rate when using TOST.
  • To propose a simple method for controlling the family-wise error rate in pairwise equivalence testing.

Main Methods:

  • Derivation of a condition to bound the family-wise error rate for TOST.
  • Demonstration of a scaling method for the nominal Type I error rate.
  • Comparison of the proposed method with the Bonferroni correction.

Main Results:

  • A condition is presented that bounds the family-wise error rate when using TOST.
  • Scaling the nominal Type I error rate by (k-1) for k independent groups controls the family-wise error rate.
  • The proposed method is less conservative than the Bonferroni correction.

Conclusions:

  • A straightforward approach exists to control family-wise error rates in pairwise equivalence testing.
  • The (k-1) scaling method offers an efficient alternative to Bonferroni correction for TOST.
  • This method enhances the reliability of equivalence testing in complex research designs.