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

Regression Analysis01:11

Regression Analysis

8.8K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
8.8K
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

9.7K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
9.7K
Regression Toward the Mean01:52

Regression Toward the Mean

7.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
7.3K
Correlation and Regression00:53

Correlation and Regression

4.0K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
4.0K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

1.2K
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
1.2K
Correlation of Experimental Data01:23

Correlation of Experimental Data

513
Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
513

You might also read

Related Articles

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

Sort by
Same author

Collaborative Inference for Accelerated Failure Time Model Using Clinical Center-Level Summary Statistics.

Statistics in medicine·2025
Same author

SUPERVISED HOMOGENEITY FUSION: A COMBINATORIAL APPROACH.

Annals of statistics·2025
Same author

Evaluation of c-Myc and Phosphorylated Glucocorticoid Receptor (p-GR) for Predicting Diabetic Foot Ulcer Healing-A Diabetic Foot Consortium Study.

Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society·2025
Same author

Uncertainty Quantification in Epigenetic Clocks via Conformalized Quantile Regression.

Genetic epidemiology·2025
Same author

Uncertainty quantification in epigenetic clocks via conformalized quantile regression.

medRxiv : the preprint server for health sciences·2024
Same author

Robust High-Dimensional Regression with Coefficient Thresholding and its Application to Imaging Data Analysis.

Journal of the American Statistical Association·2024
Same journal

Individualized dynamic latent factor model for multi-resolutional data with application to mobile health.

Biometrika·2026
Same journal

Functional principal component analysis forsparse censored data.

Biometrika·2026
Same journal

Finding distributions that differ, with false discovery rate control.

Biometrika·2026
Same journal

Sequential Gibbs posteriors with applications to principal component analysis.

Biometrika·2026
Same journal

Comparing causal parameters with many treatments and positivity violations.

Biometrika·2026
Same journal

Leveraging External Data for Testing Experimental Therapies with Biomarker Interactions in Randomized Clinical Trials.

Biometrika·2026
See all related articles

Related Experiment Video

Updated: Mar 19, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.9K

Regression analysis of networked data.

Yan Zhou1, Peter X-K Song1

  • 1Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, U.S.A. , zhouyan@umich.edu.

Biometrika
|June 10, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a new regression method for analyzing complex network data. The hybrid approach efficiently integrates prior knowledge and observed data correlations for robust analysis, particularly in neuroimaging studies.

Keywords:
Estimating functionEvent-related potentialGeneralized method of momentsHybrid quadratic inference functionShrinkage

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

2.7K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

6.1K

Related Experiment Videos

Last Updated: Mar 19, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.9K
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

2.7K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

6.1K

Area of Science:

  • Statistics
  • Biostatistics
  • Neuroimaging Analysis

Background:

  • Assessing relationships between multi-dimensional variables and network-correlated covariates presents analytical challenges.
  • Integrating network topology into regression analysis requires robust methodologies.

Purpose of the Study:

  • To propose a novel hybrid quadratic inference method for regression analysis of network-correlated data.
  • To develop an efficient method for weighting prior and data-driven network correlations.

Main Methods:

  • A hybrid quadratic inference approach combining prior and data-driven network correlations.
  • A Godambe information-based tuning strategy for optimal weight allocation.
  • Simulation studies and application to neuroimaging data.

Main Results:

  • The proposed method is conceptually simple, computationally fast, and possesses favorable large-sample properties.
  • The method effectively handles the integration of network structures in regression.
  • Demonstrated application in analyzing iron deficiency effects on infant auditory memory.

Conclusions:

  • The hybrid quadratic inference method provides an efficient and robust approach for network-based regression.
  • This methodology is applicable to complex biological and neuroimaging association studies.
  • The Godambe information-based tuning ensures estimator efficiency.