Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

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

Sort by

Same author

Siderophore-producing bacteria reduce soil cadmium bioavailability and alleviate cadmium stress in alfalfa.

Ecotoxicology and environmental safety·2026

Same author

Statistics and AI - A Fireside Conversation.

Harvard data science review·2026

Same author

An Ultrastable Hydrogen-Bonded Organic Framework With Two-Dimensional Pores for Rapid Adsorption Kinetics and Efficient Xe/Kr Separation.

Angewandte Chemie (International ed. in English)·2026

Same author

Fresh-seawater interface shapes nitrogen fate in a subtropical estuary: Insights from multi-isotopic and metagenomic analyses.

Water research·2026

Same author

Sn-Mediated Amorphous NiFeP Electroless Plating on Nickel Mesh for Stable High-Current Oxygen Evolution Reaction.

ACS applied materials & interfaces·2026

Same author

Integrating multi-stage interventions for harmful algal blooms effective management.

Journal of environmental management·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

Search research articles

Related Experiment Video

Updated: Jun 10, 2025

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning.

Chengchun Shi¹, Yunzhe Zhou², Lexin Li²

¹London School of Economics and Political Science.

Journal of the American Statistical Association

|October 17, 2024

Summary

This summary is machine-generated.

This study introduces a novel hypothesis testing method for directed acyclic graphs (DAGs). The new approach accommodates nonlinear associations and time-dependent data, enhancing causal inference in complex networks.

Keywords:

Brain connectivity networks Directed acyclic graph Generative adversarial networks Hypothesis testing Multilayer perceptron neural networks

More Related Videos

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Related Experiment Videos

Last Updated: Jun 10, 2025

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Area of Science:

Statistics
Machine Learning
Computational Neuroscience

Background:

Directed acyclic graphs (DAGs) are crucial for representing causal relationships.
Existing DAG inference methods often assume linear models and independent data, limiting their applicability.
There is a need for flexible hypothesis testing methods that handle complex data structures.

Purpose of the Study:

To propose a new hypothesis testing method for directed acyclic graphs (DAGs).
To develop a test that accommodates nonlinear associations and time-dependent data.
To provide a statistically rigorous framework for DAG inference.

Main Methods:

Utilized flexible neural network learners for hypothesis testing.
Developed a method allowing for nonlinear associations among random variables.
Established asymptotic guarantees for the test with diverging numbers of subjects or time points.

Main Results:

Demonstrated the efficacy of the proposed hypothesis testing method through simulations.
Successfully applied the test to analyze brain connectivity networks.
The method shows promise for inferring causal structures in complex, time-dependent systems.

Conclusions:

The proposed method offers a powerful new tool for hypothesis testing in directed acyclic graphs.
It overcomes limitations of existing methods by handling nonlinearities and time-dependent data.
The approach has broad implications for causal inference in various scientific domains, including neuroscience.