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

Reliability and Validity01:29

Reliability and Validity

13.3K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
13.3K
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

2.5K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.5K
Self-Evaluation Maintenance Model01:29

Self-Evaluation Maintenance Model

25
The Self-Evaluation Maintenance (SEM) model offers a psychological framework to understand how individuals’ self-esteem is influenced by the achievements of others, particularly those with whom they share close personal bonds. The SEM model operates when personal rather than social identity guides individuals. Central to this model is the notion that individuals have an inherent desire to preserve a favorable self-image, which is continuously shaped by interpersonal comparisons and...
25
Typical Model Studies01:30

Typical Model Studies

477
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
477
Goodness-of-Fit Test01:16

Goodness-of-Fit Test

5.1K
The goodness-of-fit test is a type of hypothesis test which determines whether the data "fits" a particular distribution. For example, one may suspect that some anonymous data may fit a binomial distribution. A chi-square test (meaning the distribution for the hypothesis test is chi-square) can be used to determine if there is a fit. The null and alternative hypotheses may be written in sentences or stated as equations or inequalities. The test statistic for a goodness-of-fit test is given as...
5.1K
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

369
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
369

You might also read

Related Articles

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

Sort by
Same author

To Disaggregate or Not to Disaggregate: A Focus on Covariates in Multilevel Models.

Multivariate behavioral research·2026
Same author

Detecting Transition Points in the Slope-Intercept Relation in Linear Latent Growth Models.

Multivariate behavioral research·2025
Same author

Mediators that Matter: Psychological Distress, Developmental Assets, and Educational Outcomes among Black Youth.

Journal of educational psychology·2025
Same author

Sedimentation in Saudi Arabia's 574 reservoirs: Nationwide assessment using remote sensing and erosion modeling.

Journal of environmental management·2025
Same author

nmax and the quest to restore caution, integrity, and practicality to the sample size planning process.

Psychological methods·2025
Same author

Predicting Post-Fracture Recovery with Smartphone Mobility Data: A Proof-of-Concept Study.

The Journal of bone and joint surgery. American volume·2025
Same journal

Bayesian evaluation for latent variable models: A tutorial on computing information criteria and bayes factors with the r package bleval.

Psychological methods·2026
Same journal

A stochastic block prior for clustering in graphical models.

Psychological methods·2026
Same journal

Three-level vector autoregressive models.

Psychological methods·2026
Same journal

Scaling cognitive modeling to big data: A deep learning approach to studying individual differences in evidence accumulation model parameters.

Psychological methods·2026
Same journal

Best practices in multilevel modeling for within-cluster group comparisons: An evaluation of coding strategies reflecting group composition and heterogeneity.

Psychological methods·2026
Same journal

A unified framework for psychometrics in experimental psychology: The standardized generalized hierarchical factor model.

Psychological methods·2026
See all related articles

Related Experiment Video

Updated: Oct 9, 2025

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
09:00

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Published on: August 16, 2024

951

Model-based incremental validity.

Yi Feng1, Gregory R Hancock1

  • 1Department of Human Development and Quantitative Methodology.

Psychological Methods
|December 20, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new structural equation modeling strategy to assess incremental validity, overcoming limitations of traditional regression methods. This approach enhances the evaluation of multiple predictors within a single model for improved construct validity research.

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
Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

4.6K

Related Experiment Videos

Last Updated: Oct 9, 2025

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
09:00

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Published on: August 16, 2024

951
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
Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

4.6K

Area of Science:

  • Psychometrics
  • Quantitative Psychology
  • Applied Statistics

Background:

  • Incremental validity is crucial for construct validation across disciplines.
  • Traditional multiple regression methods for assessing incremental validity have significant limitations.
  • A need exists for more robust methodologies to evaluate predictor contributions.

Purpose of the Study:

  • To present a novel structural equation modeling (SEM) strategy for assessing incremental validity.
  • To expand researchers' capabilities in evaluating individual and block predictors, both measured and latent.
  • To provide a flexible framework for complex incremental validity investigations.

Main Methods:

  • Developed SEM models for four distinct research scenarios (individual/block, measured/latent predictors).
  • Provided technical details on model specification and constraints.
  • Illustrated applications with two empirical examples using Mplus and R syntax.

Main Results:

  • The proposed SEM strategy effectively integrates the assessment of incremental validity for multiple predictors within a unified model.
  • Demonstrated the flexibility of the SEM approach for various predictor types and research designs.
  • Empirical examples confirmed the practical utility and applicability of the method.

Conclusions:

  • The SEM-based approach offers a powerful advancement over traditional methods for studying incremental validity.
  • This methodology enhances the precision and scope of construct validity assessments.
  • Researchers are provided with practical tools and syntax for implementing advanced incremental validity analyses.