Multilevel Multigroup Structural Equation Modeling in a Single-Level Framework
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| Title: | Multilevel Multigroup Structural Equation Modeling in a Single-Level Framework |
|---|---|
| Language: | English |
| Authors: | Julia-Kim Walther (ORCID |
| Source: | Structural Equation Modeling: A Multidisciplinary Journal. 2025 32(5):897-928. |
| 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: | 32 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Secondary Education |
| Descriptors: | Structural Equation Models, Hierarchical Linear Modeling, Factor Analysis, Groups, Sample Size, Achievement Tests, Foreign Countries, Secondary School Students, International Assessment |
| Geographic Terms: | Albania, Ireland |
| Assessment and Survey Identifiers: | Program for International Student Assessment |
| DOI: | 10.1080/10705511.2024.2434596 |
| ISSN: | 1070-5511 1532-8007 |
| Abstract: | Heterogeneity of variance is more than a statistical nuisance when variance parameters are of substantial interest. In multilevel modeling (e.g. students within classes), for instance, the inclusion of discrete variables at the between-cluster level (e.g. school type) may lead to the detection of differences between variances at the within-cluster level (e.g. students' performance in a test). The resulting heterogeneous variances (e.g. lower variance for students at high schools compared to grammar schools) have the potential to inform research and practice (e.g. on educational effectiveness). Along the lines of 'people are variables too', we demonstrate how the single-level formulation of multilevel structural equation models, the wide format approach (Barendse & Rosseel, 2020; Mehta & Neale, 2005), can be used in combination with multigroup modeling in order to obtain heterogeneous variance estimates. We provide evidence for the proposed WFmultigroup approaches' accuracy by means of a simulation study and showcase its application with an empirical illustration with the "lavaan" package in R. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1501490 |
| Database: | ERIC |
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| Abstract: | Heterogeneity of variance is more than a statistical nuisance when variance parameters are of substantial interest. In multilevel modeling (e.g. students within classes), for instance, the inclusion of discrete variables at the between-cluster level (e.g. school type) may lead to the detection of differences between variances at the within-cluster level (e.g. students' performance in a test). The resulting heterogeneous variances (e.g. lower variance for students at high schools compared to grammar schools) have the potential to inform research and practice (e.g. on educational effectiveness). Along the lines of 'people are variables too', we demonstrate how the single-level formulation of multilevel structural equation models, the wide format approach (Barendse & Rosseel, 2020; Mehta & Neale, 2005), can be used in combination with multigroup modeling in order to obtain heterogeneous variance estimates. We provide evidence for the proposed WFmultigroup approaches' accuracy by means of a simulation study and showcase its application with an empirical illustration with the "lavaan" package in R. |
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| ISSN: | 1070-5511 1532-8007 |
| DOI: | 10.1080/10705511.2024.2434596 |
