ERIC Number: EJ685047
Record Type: Journal
Publication Date: 2004-Mar
The Integration of Continuous and Discrete Latent Variable Models: Potential Problems and Promising Opportunities
Bauer, Daniel J.; Curran, Patrick J.
Psychological Methods, v9 n1 p3-29 Mar 2004
Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model, nonnormal continuous measures, and nonlinear relationships among observed and/or latent variables. When the objective of a SEMM analysis is the identification of latent classes, these conditions should be considered as alternative hypotheses and results should be interpreted cautiously. However, armed with greater knowledge about the estimation of SEMMs in practice, researchers can exploit the flexibility of the model to gain a fuller understanding of the phenomenon under study.
Descriptors: Structural Equation Models, Item Response Theory, Research Methodology, Computation, Data Interpretation
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Publication Type: Journal Articles; Reports - Evaluative
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