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

Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

705
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
705
Bioequivalence Data: Statistical Interpretation01:16

Bioequivalence Data: Statistical Interpretation

324
The statistical interpretation of bioequivalence data is a significant aspect of pharmaceutical research. Bioequivalence refers to the absence of any significant difference in the rate and extent to which the active ingredient in pharmaceutical products becomes available at the site of drug action when administered at the same molar dose under similar conditions. This helps determine if different drug products have similar absorption rates, ensuring their interchangeability.Statistical...
324
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

565
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
565
Multiple Comparison Tests01:13

Multiple Comparison Tests

4.6K
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...
4.6K
Test for Homogeneity01:23

Test for Homogeneity

2.5K
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...
2.5K
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

4.4K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
4.4K

You might also read

Related Articles

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

Sort by
Same author

Association of Antidiabetic Medication Classes With Survival Outcomes in Pulmonary Hypertension Patients With Diabetes.

Pulmonary circulation·2026
Same author

Risk factors for pentosan polysulfate maculopathy.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie·2026
Same author

The association between extracellular fluid volume and sympathetic nervous system activity in patients with chronic kidney disease.

American journal of physiology. Renal physiology·2025
Same author

Piezo-type mechanosensitive ion channel component 1 (PIEZO1) is upregulated in peripheral arterial disease (PAD) and a novel murine PAD model.

JVS-vascular science·2025
Same author

Sustained Benefit of Short-Term Levodopa Treatment on Inner Retinal Function in Patients With Diabetes.

Translational vision science & technology·2025
Same author

Sodium-Glucose Cotransporter-2 Inhibitor Therapy and Longitudinal Changes in Kidney Function among Veterans with Autosomal Dominant Polycystic Kidney Disease.

Clinical journal of the American Society of Nephrology : CJASN·2025
Same journal

Widening Health Inequality and Causal Metabolic Drivers in Global Colorectal Cancer: A Multi-Dimensional Study.

Cancer informatics·2026
Same journal

GFAP-Dependent Transcriptional Dynamics and Cellular Heterogeneity in Primary, Recurrent, and Grade III Gliomas.

Cancer informatics·2026
Same journal

Translating Data Into Clinical Tools: An Integrative Strategy for Precision Biomarker Identification in Soft Tissue Sarcoma Diagnosis and Prognosis.

Cancer informatics·2026
Same journal

The MAPK Pathway Coordinates an Immunosuppressive Microenvironment in Colorectal Cancer: A Single-Cell Guided Prognostic Model.

Cancer informatics·2026
Same journal

Multi-Scale Cross-Attention Multiple Instance Learning Network for Automated Classification of Colorectal Polyps.

Cancer informatics·2026
Same journal

LEPR Contributes to Lung Squamous Cell Carcinoma: Insights From Mendelian Randomization and Experimental Studies.

Cancer informatics·2026
See all related articles

Related Experiment Video

Updated: Mar 29, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

4.1K

Multigroup Equivalence Analysis for High-Dimensional Expression Data.

Celeste Yang1, Alfred A Bartolucci2, Xiangqin Cui2

  • 1Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Ryals School of Public Health, Birmingham, AL, USA. ; BioFire Diagnostics, LLC, Salt Lake City, UT, USA.

Cancer Informatics
|December 3, 2015
PubMed
Summary
This summary is machine-generated.

Two equivalence tests, the F-test and range test, show moderate power for analyzing gene expression microarray data. The F-test generally outperforms the range test, with both offering interpretable equivalence limits.

Keywords:
F-testequivalencehigh dimensionmultiple groupprostate cancerrange test

More Related Videos

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

4.9K
A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

18.5K

Related Experiment Videos

Last Updated: Mar 29, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

4.1K
High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

4.9K
A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

18.5K

Area of Science:

  • Genomics
  • Biostatistics
  • Bioinformatics

Background:

  • Equivalence tests are established in bioequivalence and acceptance sampling.
  • Their use in high-dimensional gene expression data analysis is emerging.
  • Microarray data analysis requires robust statistical methods for hypothesis testing.

Purpose of the Study:

  • To evaluate the performance of two multigroup equivalence tests (F-test and range test) on gene expression microarray data.
  • To adapt existing equivalence tests to the difference ratio criterion.
  • To identify genes with specific expression trajectories in prostate cancer stages.

Main Methods:

  • Adaptation of the F-test and range test for multigroup equivalence testing.
  • Application of the difference ratio as an equivalence criterion.
  • Simulation studies to assess test power and type I error control.
  • Analysis of a prostate cancer microarray dataset.

Main Results:

  • Both F-test and range test demonstrated moderate power and controlled type I error rates.
  • The F-test was more powerful than the range test across simulated parameters.
  • Power was comparable between the F-test and range test when comparing three groups.
  • The tests successfully identified genes with prespecified expression trajectories in prostate cancer.

Conclusions:

  • Multigroup equivalence tests, particularly the F-test, are effective for analyzing gene expression microarray data.
  • These methods provide easily interpretable equivalence limits.
  • The adapted tests can identify biologically relevant gene expression patterns, such as those in cancer progression.