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

Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

4.0K
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...
4.0K
Sample Proportion and Population Proportion01:20

Sample Proportion and Population Proportion

6.9K
Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
6.9K
True Stress and True Strain01:28

True Stress and True Strain

858
Engineering stress is calculated as the load divided by the original, undeformed cross-sectional area. It approximates a material under load. This approximation is especially relevant post-yield in ductile materials. Though engineering stress-strain diagrams are often used for their convenience and accessibility, they can sometimes fall short in accuracy, particularly when dealing with large strain values.
In contrast, true stress offers a more precise portrayal. It is computed by dividing the...
858
Multiple Comparison Tests01:13

Multiple Comparison Tests

4.5K
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...
4.5K
Null and Alternative Hypotheses01:16

Null and Alternative Hypotheses

12.8K
The actual hypothesis testing begins by considering two hypotheses. They are termed  the null hypothesis and the alternative hypothesis. These hypotheses contain opposing viewpoints.
The null hypothesis, denoted by H0 is a statement of no difference between the variables—they are not related. This can often be considered the status quo. As  a result if you cannot accept the null, it requires some action.
The alternative hypothesis, denoted by H1 or Ha, is a claim about the...
12.8K
Discrete Fourier Transform01:15

Discrete Fourier Transform

922
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
922

You might also read

Related Articles

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

Sort by
Same author

Inflammation impacts androgen receptor signaling in basal prostate stem cells through interleukin 1 receptor antagonist.

Communications biology·2024
Same author

Inflammation Impacts Androgen Receptor Signaling in Basal Prostate Stem Cells Through Interleukin 1 Receptor Antagonist.

Research square·2024
Same author

Efficient Multiple Imputation for Sensitivity Analysis of Recurrent Events Data with Informative Censoring.

Statistics in biopharmaceutical research·2022
Same author

Inbreeding Depression in Genotypically Matched Diploid and Tetraploid Maize.

Frontiers in genetics·2020
Same author

Comments on Dr. Aniket Biswas' Letter to the Editor.

Biometrical journal. Biometrische Zeitschrift·2020
Same author

A weighted FDR procedure under discrete and heterogeneous null distributions.

Biometrical journal. Biometrische Zeitschrift·2020

Related Experiment Video

Updated: Feb 10, 2026

Computerized Adaptive Testing System of Functional Assessment of Stroke
05:21

Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

6.3K

Multiple testing with discrete data: Proportion of true null hypotheses and two adaptive FDR procedures.

Xiongzhi Chen1, Rebecca W Doerge2, Joseph F Heyse3

  • 1Department of Mathematics and Statistics, Washington State University, Pullman, WA, USA.

Biometrical Journal. Biometrische Zeitschrift
|May 12, 2018
PubMed
Summary

This study introduces a novel estimator for true null hypotheses, improving false discovery rate (FDR) control with discrete p-values. Adaptive procedures based on this estimator offer greater statistical power in multiple testing scenarios.

Keywords:
discrete p valuesfalse discovery rateheterogeneous null distributionsmultiple hypotheses testingproportion of true null hypotheses

More Related Videos

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

4.3K
Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat
06:03

Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat

Published on: September 20, 2016

15.3K

Related Experiment Videos

Last Updated: Feb 10, 2026

Computerized Adaptive Testing System of Functional Assessment of Stroke
05:21

Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

6.3K
An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

4.3K
Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat
06:03

Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat

Published on: September 20, 2016

15.3K

Area of Science:

  • Statistics
  • Biostatistics
  • Genomics

Background:

  • Multiple testing is common in high-throughput studies.
  • Controlling the false discovery rate (FDR) is crucial for reliable results.
  • Existing methods struggle with discrete and heterogeneous null distributions of p-values.

Purpose of the Study:

  • To develop a new, less biased estimator for the proportion of true null hypotheses.
  • To introduce adaptive procedures for FDR control using the novel estimator.
  • To evaluate the performance of these adaptive procedures compared to existing methods.

Main Methods:

  • Proposed a novel estimator for the proportion of true null hypotheses.
  • Developed adaptive Benjamini-Hochberg (aBH) and adaptive Benjamini-Hochberg-Heyse (aBHH) procedures.
  • Conducted simulation studies and applied procedures to HIV vaccine efficacy data.

Main Results:

  • The new estimator showed reduced upward bias compared to Storey's and other estimators.
  • Adaptive procedures (aBH, aBHH) demonstrated increased power over nonadaptive counterparts.
  • The aBHH procedure was generally more powerful than aBH and randomized p-value procedures.

Conclusions:

  • The proposed adaptive procedures offer improved power for FDR control with discrete p-values.
  • The novel estimator and adaptive methods are effective in identifying differentially polymorphic positions in genetic studies.
  • These methods enhance the discovery potential in complex biological datasets while maintaining FDR control.