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

Multiple Regression01:25

Multiple Regression

3.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.0K
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

150
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
150
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

107
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
107
Modeling and Similitude01:12

Modeling and Similitude

268
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
268
Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
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...
6.3K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

72
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
72

You might also read

Related Articles

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

Sort by
Same author

Tobacco Use and Cessation Strategies Among Individuals Recently Diagnosed with Cancer.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco·2026
Same author

Batch Effect Correction for Neuroimaging Data with Heterogeneous Spatial Correlations.

bioRxiv : the preprint server for biology·2026
Same author

Proposal for Circadian Rhythms and Their Behavioral Outputs as Biomarkers in <i>DSM-6</i>: Response to Cuthbert et al.

The American journal of psychiatry·2026
Same author

Rejoinder to the discussion on "INTACT: A method for integration of longitudinal physical activity data from multiple sources".

Biometrics·2026
Same author

An open, fully-processed data resource for studying mood and sleep variability in the developing brain.

Aperture neuro·2026
Same author

INTACT: a method for integration of longitudinal physical activity data from multiple sources.

Biometrics·2026
Same journal

A Bayesian functional concurrent zero-inflated Dirichlet-multinomial regression model with application to infant microbiome.

Biostatistics (Oxford, England)·2026
Same journal

Towards optimal environmental policies: policy learning under arbitrary bipartite network interference.

Biostatistics (Oxford, England)·2026
Same journal

Multilevel functional quantile principal component analysis.

Biostatistics (Oxford, England)·2026
Same journal

Adaptive transfer learning for time-to-event modeling with applications in disease risk assessment.

Biostatistics (Oxford, England)·2026
Same journal

High-dimensional test for one-sided hypotheses.

Biostatistics (Oxford, England)·2026
Same journal

NBSR: a Negative Binomial Softmax Regression model for microRNA-seq data analysis.

Biostatistics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jul 9, 2025

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.0K

Similarity-based multimodal regression.

Andrew A Chen1, Sarah M Weinstein2, Azeez Adebimpe3,4

  • 1Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC 29425, USA.

Biostatistics (Oxford, England)
|December 7, 2023
PubMed
Summary
This summary is machine-generated.

We developed a new method, Similarity-based Multimodal Regression (SiMMR), to analyze diverse health data types simultaneously. SiMMR effectively identifies associations between clinical variables and complex multimodal data, even with limited samples.

Keywords:
distance statisticsmobile healthmultimodalneuroimaging

More Related Videos

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.8K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.5K

Related Experiment Videos

Last Updated: Jul 9, 2025

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.0K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.8K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.5K

Area of Science:

  • Biostatistics
  • Computational Biology
  • Data Science

Background:

  • Complex human phenotypes require analyzing diverse data types like imaging and mobile health.
  • Existing methods struggle to integrate multimodal data with different structures and dimensions.
  • Multivariate distance matrix regression handles single data types but not multiple complementary ones.

Purpose of the Study:

  • To introduce a novel distance-based regression model for simultaneous analysis of multiple data modalities.
  • To enable regression across complementary data types with differing properties and dimensionalities.
  • To address limitations in current multimodal data fusion techniques.

Main Methods:

  • Proposed Similarity-based Multimodal Regression (SiMMR), a novel distance-based regression framework.
  • Utilized distance profiles for simultaneous regression of multiple modalities.
  • Evaluated method performance using simulations, imaging studies, and longitudinal mobile health data.

Main Results:

  • SiMMR successfully detected associations between clinical variables and multimodal data.
  • The method demonstrated effectiveness even with modest sample sizes.
  • Experimental results provided insights into various test statistics for SiMMR application.

Conclusions:

  • SiMMR offers a powerful new approach for analyzing complex multimodal health data.
  • The method facilitates the integration of diverse data structures and dimensions.
  • Recommendations are provided for applying SiMMR across various research scenarios.