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

Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

748
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
748
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

1.6K
Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...
1.6K
Components of Stress01:23

Components of Stress

536
Stress analysis under multiple loading conditions is intricate, necessitating a comprehensive grasp of normal and shearing stresses. Consider a small cube at point O, subjected to stress on all six faces, visible or not. Normal stress components σx, σy, σz act perpendicularly to the x, y, and z axes. Shearing stress components τxy and τxz are exerted on faces perpendicular to these axes.
Interestingly, the hidden cube faces also experience these stresses, equal and...
536
Components of Language01:24

Components of Language

820
Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
820
Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

1.0K
Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
1.0K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.5K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.5K

You might also read

Related Articles

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

Sort by
Same author

Longitudinal Associations Between Inflammation and Multi-Dimensional Fatigue up to 2 Years After Colorectal Cancer Diagnosis.

International journal of cancer·2026
Same author

Manganese-based cathode materials for aqueous zinc-ion batteries: a mini review.

Nanoscale·2026
Same author

Detection of rare medical events in electronic health records using machine learning: Current practices and suggestions - A scoping review.

PloS one·2026
Same author

Exploratory structural equation modeling and the curse of dimensionality.

Behavior research methods·2026
Same author

Effects of Cancer Treatment on Inflammation in Colorectal Cancer Patients: A Longitudinal Study.

Clinical colorectal cancer·2026
Same author

Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort study.

EClinicalMedicine·2025
Same journal

Planned missingness in intensive longitudinal studies: Extensions and comparisons of multiform designs.

Behavior research methods·2026
Same journal

A validity-guided workflow for robust large language model research in psychology.

Behavior research methods·2026
Same journal

Are 7-point Likert scales preferable to 5-point scales in language research?

Behavior research methods·2026
Same journal

Generative psychometrics via AI-GENIE: Automatic item generation and validation with network-integrated evaluation.

Behavior research methods·2026
Same journal

Exploring psychological tradeoffs: Developing and demonstrating an R Shiny app for Pareto optimization.

Behavior research methods·2026
Same journal

The performance of Bayesian fit measures in detecting misspecified multilevel structural equation modeling.

Behavior research methods·2026
See all related articles

Related Experiment Video

Updated: Feb 1, 2026

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI
10:35

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI

Published on: June 3, 2013

33.3K

RegularizedSCA: Regularized simultaneous component analysis of multiblock data in R.

Zhengguo Gu1, Katrijn Van Deun2

  • 1Department of Methodology and Statistics, TSB, Tilburg University, PO Box 90153, 5000LE, Tilburg, The Netherlands. z.gu@tilburguniversity.edu.

Behavior Research Methods
|December 14, 2018
PubMed
Summary
This summary is machine-generated.

This R package integrates multiple data sources using simultaneous component analysis (SCA) and structured variable selection. It identifies shared and specific variations, enabling flexible component matrix estimation for diverse research fields.

Keywords:
Common/distinctive componentsGroup LassoLassoLinked data analysisMultiblock analysisSimultaneous component analysis

More Related Videos

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.4K
Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

3.3K

Related Experiment Videos

Last Updated: Feb 1, 2026

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI
10:35

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI

Published on: June 3, 2013

33.3K
Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.4K
Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

3.3K

Area of Science:

  • Data Science
  • Statistical Computing
  • Multivariate Analysis

Background:

  • Linked data from diverse sources are common in many scientific disciplines.
  • Analyzing these multiple data blocks presents unique challenges.
  • Existing methods may not adequately capture shared and specific variations across sources.

Purpose of the Study:

  • Introduce a novel R package for integrated analysis of multiple data blocks.
  • Provide tools for identifying joint and specific variations across linked data.
  • Facilitate flexible estimation of component matrices with predefined structures.

Main Methods:

  • The package implements methods combining Simultaneous Component Analysis (SCA) with structured variable selection.
  • It allows for the identification of shared variation across all data sources.
  • It enables the identification of specific variation associated with subsets of data sources.

Main Results:

  • The developed R package successfully integrates data from multiple sources.
  • It effectively distinguishes between joint and specific variations.
  • The package allows for flexible estimation of component matrices with user-defined structures.

Conclusions:

  • The R package offers a powerful tool for integrated analysis of linked data.
  • It is applicable across various scientific fields, including biomedical research, genomics, and social sciences.
  • The package is expected to be valuable for multidisciplinary research involving multiple data sources.