Multilevel Factor Mixture Modeling: A Tutorial for Multilevel Constructs
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| Title: | Multilevel Factor Mixture Modeling: A Tutorial for Multilevel Constructs |
|---|---|
| Language: | English |
| Authors: | Chunhua Cao (ORCID |
| Source: | Structural Equation Modeling: A Multidisciplinary Journal. 2025 32(1):155-171. |
| Availability: | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Peer Reviewed: | Y |
| Page Count: | 17 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Descriptive |
| Descriptors: | Hierarchical Linear Modeling, Factor Analysis, Nonparametric Statistics, Statistical Analysis, Models, Measurement, Equations (Mathematics), Data |
| DOI: | 10.1080/10705511.2024.2332257 |
| ISSN: | 1070-5511 1532-8007 |
| Abstract: | Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterogeneity at the within level, between level, or both levels. This tutorial focuses on explicating the model specification of multilevel FMM that considers the conceptualization of multilevel constructs. Empirical data sets are used to demonstrate the applications of multilevel FMM for within-level constructs, between-level constructs, and within- and between-level constructs. Detailed model specifications of integrating latent classes into multilevel constructs are provided. For modeling the heterogeneity at the between level, parametric and nonparametric approaches are compared both conceptually and substantively using demonstration data. The interpretations of results using multilevel FMM are also provided. The tutorial is concluded with a discussion of some important aspects of applying multilevel FMM. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1457243 |
| Database: | ERIC |
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| Abstract: | Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterogeneity at the within level, between level, or both levels. This tutorial focuses on explicating the model specification of multilevel FMM that considers the conceptualization of multilevel constructs. Empirical data sets are used to demonstrate the applications of multilevel FMM for within-level constructs, between-level constructs, and within- and between-level constructs. Detailed model specifications of integrating latent classes into multilevel constructs are provided. For modeling the heterogeneity at the between level, parametric and nonparametric approaches are compared both conceptually and substantively using demonstration data. The interpretations of results using multilevel FMM are also provided. The tutorial is concluded with a discussion of some important aspects of applying multilevel FMM. |
|---|---|
| ISSN: | 1070-5511 1532-8007 |
| DOI: | 10.1080/10705511.2024.2332257 |
