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

Sampling Plans01:23

Sampling Plans

228
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
228
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

3.4K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
3.4K
Test for Homogeneity01:23

Test for Homogeneity

2.0K
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...
2.0K
Stratified Sampling Method01:16

Stratified Sampling Method

12.1K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
12.1K
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

4.1K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
4.1K
Bonferroni Test01:10

Bonferroni Test

2.8K
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...
2.8K

You might also read

Related Articles

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

Sort by
Same author

Efficacy of a Moisture-Wicking, Silver-Impregnated Textile in Hospitalized Patients With Intertriginous Dermatitis (ITD): A Single-Case Experiment.

Journal of wound, ostomy, and continence nursing : official publication of The Wound, Ostomy and Continence Nurses Society·2026
Same author

Drug Development.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Corrigendum to "Days alive out of hospital in heart failure: Insights from the PARADIGM-HF and CHARM trials" [Am Heart J 241 (2021) 108-119].

American heart journal·2025
Same author

NLAS-multi: A multilingual corpus of automatically generated Natural Language Argumentation Schemes.

Data in brief·2024
Same author

Implementing the Brøset Violence Checklist in the ED.

The American journal of nursing·2024
Same author

Small bowel lipoma and intussusception: a case report.

Journal of surgical case reports·2024
Same journal

Correction.

Journal of biopharmaceutical statistics·2026
Same journal

Leveraging external controls in clinical trials: estimands, estimation, assumptions.

Journal of biopharmaceutical statistics·2026
Same journal

Special issue of nonclinical statistics in regulatory applications guest editors' notes.

Journal of biopharmaceutical statistics·2026
Same journal

Comparison of flexible parametric modeling and nonparametric methods to estimate restricted mean survival time: A simulation study.

Journal of biopharmaceutical statistics·2026
Same journal

Simulated treatment comparisons with jackknife pseudo values for estimating population-adjusted marginal treatment effects.

Journal of biopharmaceutical statistics·2026
Same journal

Sample sizes for randomized controlled trials utilizing Bayesian response adaptive randomization for continuous outcomes.

Journal of biopharmaceutical statistics·2026
See all related articles

Related Experiment Video

Updated: Aug 7, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.6K

Step-down multiple testing procedures for the overall population and partitioning subgroups.

John Lawrence1

  • 1Office of Biostatistics, US Food and Drug Administration, Silver Spring, Maryland,USA.

Journal of Biopharmaceutical Statistics
|March 8, 2023
PubMed
Summary
This summary is machine-generated.

This study presents multiple comparison procedures for two-armed clinical trials with ordered hypotheses. These methods control the family-wise error rate for testing overall and subgroup treatment effects.

Keywords:
Bonferroniclosure principlegatekeeping tests

More Related Videos

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.2K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.6K

Related Experiment Videos

Last Updated: Aug 7, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.6K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.2K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.6K

Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Statistical Inference

Background:

  • Testing treatment effects in subgroups requires careful statistical consideration.
  • Subgroup definitions can be based on disease etiology or patient characteristics like genetics, age, sex, or race.
  • Differential treatment effects across subgroups are common.

Purpose of the Study:

  • To describe multiple comparison procedures for two-armed studies.
  • To address scenarios with a primary hypothesis and ordered secondary hypotheses.
  • To control the family-wise error rate (FWER) for overall and subgroup analyses.

Main Methods:

  • Development of statistical procedures for multiple comparisons.
  • Application to two-armed studies with hierarchical hypotheses.
  • Focus on partitioning the population into non-overlapping subgroups.

Main Results:

  • Procedures are presented that control the family-wise error rate (FWER) in the strong sense.
  • The methods are applicable when testing for treatment effects in the overall population and/or defined subgroups.
  • The procedures maintain statistical rigor under complex hypothesis structures.

Conclusions:

  • The described multiple comparison procedures offer a robust framework for analyzing subgroup effects in clinical trials.
  • These methods ensure reliable conclusions by controlling the overall error rate.
  • The approach is valuable for studies investigating differential treatment efficacy across patient populations.