Latent Class Analysis with Measurement Invariance Testing
Simulation Study to Compare Overall Likelihood Ratio vs Residual Fit Statistics Based Model Selection
Bibliographic Data
| ID | 21641805 |
|---|---|
| Authors | Zsuzsa Bakk (0000-0001-9352-4812, Leiden University, corresponding author) |
| Year | 2024 |
| Volume | 31 |
| Issue | 2 |
| Pages | 253-264 |
| Publication date | 2024-03-03 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Structural Equation Modeling: A Multidisciplinary Journal (JOURNAL) |
| Journal identifiers | ISSN: 1070-5511 • E-ISSN: 1532-8007 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/10705511.2023.2233115 |
| OpenAlex | W4386054967 |
| Language | EN |
| Citations received | 3 |
| References cited | 31 |
A standard assumption of latent class (LC) analysis is conditional independence, that is the items of the LC are independent of the covariates given the LCs. Several approaches have been proposed for identifying violations of this assumption. The recently proposed likelihood ratio approach is compared to residual statistics (bivariate residuals [BVR] and expected parameter change [EPC] statistics) for identifying nonuniform direct effect of covariates on the items of the LC model. The simulation study results show that the likelihood ratio (LR) test correctly identifies direct effects more often than the BVR statistics, showing comparable results to the EPC statistic in many situations- this at the price of having also a higher false positive rate than BVR. A real data example illustrates the use of the three procedures. Overall the combined use of residual statistics and LR testing is recommended for applied research
Algorithm · Bivariate analysis · Conditional independence · Covariate · Econometrics · Item response theory · Latent class model · Likelihood-ratio test · Maximum likelihood · Model selection · Psychometrics · Residual · Restricted maximum likelihood · Statistic · Statistical hypothesis testing · Statistics · Test statistic · Advanced Statistical Methods and Models · Mathematics
Latent Class Analysis
Covariates and Mixture Modeling
Basic Concepts and Procedures in Single- and Multiple-Group Latent Class Analysis
Prediction from Latent Classes
Robustness of Stepwise Latent Class Modeling With Continuous Distal Outcomes
Auxiliary Variables in Mixture Modeling
How to Perform Three-Step Latent Class Analysis in the Presence of Measurement Non-Invariance or Differential Item Functioning
Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials
Some New Covariance Structure Model Improvement Statistics
Investigating a typology of trust orientations towards national and European institutions
Qualitative variance, entropy, and correlation ratios for nominal dependent variables
Estimating the Association between Latent Class Membership and External Variables Using Bias-adjusted Three-step Approaches
What do Europeans Believe to be the Causes of Poverty? A Multilevel Analysis of Heterogeneity Within and Between Countries
Latent Class Modeling with Covariates
Evaluating Measurement Invariance in Categorical Data Latent Variable Models with the EPC-Interest
Evaluating Sensitivity of Parameters of Interest to Measurement Invariance in Latent Variable Models
Measurement Equivalence in Solidarity Attitudes in Europe
The Analysis of Systems of Qualitative Variables When Some of the Variables Are Unobservable. Part I-A Modified Latent Structure Approach
Latent Class Factor and Cluster Models, Bi-Plots, and Related Graphical Displays
Comparing Typological Structures Across Cultures By Multigroup Latent Class Analysis
| Citations per year | 3 |
|---|---|
| Citation span | 2025 - 2026 (2) |
| Highly cited | No |