Studying Factorial Invariance With Nominal Items
A Note on a Latent Variable Modeling Procedure
Bibliographic Data
| ID | 20283943 |
|---|---|
| Authors | Tenko Raykov (0000-0002-8911-5116, Michigan State University, East Lansing, USA, corresponding author) |
| Year | 2025 |
| Volume | 85 |
| Issue | 2 |
| Pages | 277-290 |
| Publication date | 2025-04-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Educational and Psychological Measurement (JOURNAL) |
| Journal identifiers | ISSN: 0013-1644 • E-ISSN: 1552-3888 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/00131644241256626 |
| PMID | 39563848 |
| OpenAlex | W4399981182 |
| Language | EN |
| References cited | 20 |
A latent variable modeling procedure for studying factorial invariance and differential item functioning for multi-component measuring instruments with nominal items is discussed. The method is based on a multiple testing approach utilizing the false discovery rate concept and likelihood ratio tests. The procedure complements the Revuelta, Franco-Martinez, and Ximenez approach to factorial invariance examination, and permits localization of individual invariance violations. The outlined method does not require the selection of a reference observed variable and is illustrated with empirical data
Confirmatory factor analysis · Differential item functioning · Econometrics · Factorial · Factorial experiment · Goodness of fit · Item response theory · Latent variable · Latent variable model · Measurement invariance · Psychometrics · Statistics · Structural equation modeling · Variable (mathematics) · Advanced Statistical Modeling Techniques · Mathematics · Optimal Experimental Design Methods · Psychometric Methodologies and Testing
Statistical Approaches to Measurement Invariance
Multiple-Group Invariance with Categorical Outcomes Using Updated Guidelines
Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance
Controlling the False Discovery Rate
Structural Equations with Latent Variables
Measurement Invariance is Not Sufficient for Meaningful and Valid Group Comparisons
Why Full, Partial, or Approximate Measurement Invariance Are Not a Prerequisite for Meaningful and Valid Group Comparisons
Nominal Factor Analysis of Situational Judgment Tests
Studying Differential Item Functioning via Latent Variable Modeling
Factorial Invariance in Multiple Populations
Examining Measurement Invariance and Differential Item Functioning With Discrete Latent Construct Indicators
Conducting Measurement Invariance Tests with Ordinal Data
Estimating item parameters and latent ability when responses are scored in two or more nominal categories
| Citation velocity | historical |
|---|---|
| Highly cited | No |