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

Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

450
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
450
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

3.7K
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...
3.7K
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

3.3K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
3.3K
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

700
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
700
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

407
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...
407
Hazard Ratio01:12

Hazard Ratio

435
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
435

You might also read

Related Articles

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

Sort by
Same author

MSR1 Drives MASLD Progression Via Disrupting FoxO3a-SOD3 Mediated Redox Balance in Liver Macrophages.

Liver international : official journal of the International Association for the Study of the Liver·2026
Same author

A Pseudotime-Dependent TWAS Framework Identifies Disease Genes along Cell Developmental Paths.

HGG advances·2026
Same author

Application of Terahertz Technology in Food Safety: Rice Origin-Variety Classification Based on Spectral Analysis and Machine Learning.

Foods (Basel, Switzerland)·2026
Same author

Hyaluronic acid-camouflaged dendritic silica nanoparticles enable targeted cuproptosis and photothermal therapy for lung cancer.

Colloids and surfaces. B, Biointerfaces·2026
Same author

A progenitor cell population contributes to prenatal injury repair and neonatal antimicrobial defense in the small intestine.

Cell reports·2026
Same author

Characterizing Ethnomedicinal <i>Tetrastigma hemsleyanum</i> Diels et Gilg Grown Under Different Cultivation Methods Using Stable Isotopes and Elemental Analyses.

Plants (Basel, Switzerland)·2026
Same journal

Instrumental Variable Estimation of Marginal Structural Mean Models for Time-Varying Treatment.

Journal of the American Statistical Association·2026
Same journal

Semiparametric Joint Modeling for Survival Analysis with Longitudinal Covariates.

Journal of the American Statistical Association·2026
Same journal

Dimension Reduction for Large-Scale Federated Data: Statistical Rate and Asymptotic Inference.

Journal of the American Statistical Association·2026
Same journal

Facilitating Heterogeneous Effect Estimation via Statistically Efficient Categorical Modifiers.

Journal of the American Statistical Association·2026
Same journal

Nonparametric Density Estimation of a Long-Term Trend from Repeated Semicontinuous Data.

Journal of the American Statistical Association·2026
Same journal

Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Clinicogenomic Data.

Journal of the American Statistical Association·2026
See all related articles

Related Experiment Video

Updated: Dec 7, 2025

A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

171

Likelihood ratio tests for a large directed acyclic graph.

Chunlin Li1, Xiaotong Shen1, Wei Pan2

  • 1School of Statistics, University of Minnesota, Minneapolis, MN 55455.

Journal of the American Statistical Association
|September 25, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces new statistical tests for inferring gene network connections and directionality. These methods help uncover specific gene pathways, crucial for understanding biological processes like Alzheimer's disease.

Keywords:
Directed acyclic graphL0-regularizationgene networkhigh-dimensional inferencenonconvex minimization

More Related Videos

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.5K
Detection of Homologous Recombination Intermediates via Proximity Ligation and Quantitative PCR in Saccharomyces cerevisiae
07:55

Detection of Homologous Recombination Intermediates via Proximity Ligation and Quantitative PCR in Saccharomyces cerevisiae

Published on: September 11, 2022

2.1K

Related Experiment Videos

Last Updated: Dec 7, 2025

A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

171
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.5K
Detection of Homologous Recombination Intermediates via Proximity Ligation and Quantitative PCR in Saccharomyces cerevisiae
07:55

Detection of Homologous Recombination Intermediates via Proximity Ligation and Quantitative PCR in Saccharomyces cerevisiae

Published on: September 11, 2022

2.1K

Area of Science:

  • Statistics
  • Bioinformatics
  • Genomics

Background:

  • Inferring directional relationships in biological networks, like gene regulatory networks, is crucial but lacks robust inferential tools.
  • Frequentist inference for directionality in regulatory models is an underexplored area, hindering biological pathway discovery.

Purpose of the Study:

  • To propose constrained likelihood ratio tests for inferring connectivity and directionality in Gaussian directed acyclic graphs (DAGs).
  • To derive asymptotic distributions for these tests in high-dimensional settings and develop a computational method for their application.

Main Methods:

  • Development of constrained likelihood ratio tests for connectivity and directionality in Gaussian DAGs.
  • Derivation of asymptotic distributions under high-dimensional conditions.
  • Integration of alternating direction method of multipliers and difference convex programming for computational implementation.

Main Results:

  • Asymptotic distributions for connectivity tests are chi-squared or normal.
  • Asymptotic distributions for directionality tests are the minimum of d independent chi-squared variables or a generalized Gamma distribution.
  • Power analysis and simulations confirm the tests' effectiveness in achieving inferential objectives.

Conclusions:

  • The proposed constrained likelihood ratio tests provide a powerful new tool for inferring connectivity and directionality in biological networks.
  • The computational method facilitates the practical application of these tests.
  • The method's utility is demonstrated through an analysis of an Alzheimer's disease gene expression dataset, aiding in directed pathway inference.