Cross-Level Invariance in Multilevel Factor Models. Issue 4 (4th July 2019)

• Record Type: Journal Article
• Authors: Jak, Suzanne
• Is Part Of: Structural equation modeling. Volume 26:Issue 4(2019)
• Page Start: 607
• Page End: 622
• Publication Date: 2019-07-04
• Subjects: cross-level invariance -- multilevel CFA -- multilevel SEM; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2018.1534205
• Languages: English
• ISSNs: 1070-5511

Abstract

Abstract : When modeling latent variables at multiple levels, it is important to consider the meaning of the latent variables at the different levels. If a higher-level common factor represents the aggregated version of a lower-level factor, the associated factor loadings will be equal across levels. However, many researchers do not consider cross-level invariance constraints in their research. Not applying these constraints when in fact they are appropriate leads to overparameterized models, and associated convergence and estimation problems. This simulation study used a two-level mediation model on common factors to show that when factor loadings are equal in the population, not applying cross-level invariance constraints leads to more estimation problems and smaller true positive rates. Some directions for future research on cross-level invariance in MLSEM are discussed.