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

Variation01:19

Variation

7.2K
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
7.2K
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

296
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...
296
Multiple Regression01:25

Multiple Regression

3.2K
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...
3.2K
Variability: Analysis01:11

Variability: Analysis

189
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
189
Two-Way ANOVA01:17

Two-Way ANOVA

2.8K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
2.8K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

85
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
85

You might also read

Related Articles

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

Sort by
Same author

Substance Use Among US Adults at Midlife: Risk Factors and Protective Factors Among National and Milwaukee Black American Samples.

Journal of addiction medicine·2026
Same author

Religiosity and Spirituality as Stressors or Stress Relievers in relation to Sleep Health among African American Women.

Sleep·2026
Same author

Toward the Development of a Multilevel Measure of Structural Racism: Theory and Methods.

American journal of epidemiology·2026
Same author

Correction: Identifying High-Priority Ecological-Level Indicators of Structural Racism in Black and Hispanic/Latino Communities.

Journal of racial and ethnic health disparities·2026
Same author

Food & Beverage Industry Activities That Influence Population Health: Development of the HEALTH-CORP-FB Typology.

International journal of social determinants of health and health services·2026
Same author

Identifying High-Priority Ecological-Level Indicators of Structural Racism in Black and Hispanic/Latino Communities.

Journal of racial and ethnic health disparities·2026
Same journal

A Simple Approach for Differential Test Functioning Based on Sum Scores.

Educational and psychological measurement·2026
Same journal

Evaluating Factor Retention in Large Factor Analysis Models: A Simulation Study Comparing 15 Methods.

Educational and psychological measurement·2026
Same journal

Agreement and Alignment in Binary Rating Tasks: Strategic Convergence as an Equilibrium Outcome.

Educational and psychological measurement·2026
Same journal

Interactions Between Termination Criteria and Ability Estimators in Computerized Adaptive Testing.

Educational and psychological measurement·2026
Same journal

Identification and Diagnosis of Misreporting in Surveys.

Educational and psychological measurement·2026
Same journal

The Aggregated Latent Profile Index: Measuring Person Profile Differentiation Within a Bootstrap-Validated Latent Profile Space.

Educational and psychological measurement·2026
See all related articles

Related Experiment Video

Updated: Sep 9, 2025

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.4K

Proportion Explained Component Variance in Second-Order Scales: A Note on a Latent Variable Modeling Approach.

Tenko Raykov1, Christine DiStefano2, Yusuf Ransome3

  • 1Michigan State University, East Lansing, MI, USA.

Educational and Psychological Measurement
|August 29, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to assess how much variance in behavioral scale components is explained by an underlying trait. This index complements existing measures and offers a robust way to evaluate scale psychometrics.

Keywords:
confirmatory factor analysisconstructomega-hierarchical coefficientproportion explained variancesecond-order scale

More Related Videos

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.0K
Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
06:33

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding

Published on: October 11, 2018

6.9K

Related Experiment Videos

Last Updated: Sep 9, 2025

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.4K
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.0K
Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
06:33

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding

Published on: October 11, 2018

6.9K

Area of Science:

  • Psychometrics
  • Behavioral Science
  • Statistical Modeling

Background:

  • Evaluating the variance explained by underlying traits in behavioral scales is crucial for psychometric assessment.
  • Existing methods like omega-hierarchical coefficients have limitations in fully capturing explained variance.
  • Second-order factor structures are common in complex behavioral scales.

Purpose of the Study:

  • To outline a procedure for evaluating the proportion of explained component variance by the underlying trait in behavioral scales with second-order structure.
  • To introduce a novel index as a complement to conventional psychometric coefficients.
  • To describe a point and interval estimation method for this new index.

Main Methods:

  • Utilizes confirmatory factor analysis (CFA) within latent variable modeling.
  • Develops a procedure for calculating the proportion of explained variance across scale components.
  • Employs a point and interval estimation technique for the proposed index.

Main Results:

  • The proposed index effectively quantifies the proportion of variance explained by the underlying trait.
  • This index serves as an informative complement to omega-hierarchical coefficients and explained component correlation.
  • The estimation method is practical and can be implemented using standard statistical software.

Conclusions:

  • The developed procedure provides a valuable tool for assessing the psychometric properties of behavioral scales.
  • The new index enhances the understanding of how well underlying traits account for variance in scale components.
  • This method supports rigorous evaluation of scale reliability and validity in research.