NDLI: Evaluation of Structural Equation Mixture Models: Parameter Estimates and Correct Class Assignment

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Evaluation of Structural Equation Mixture Models: Parameter Estimates and Correct Class Assignment

Content Provider	Scilit
Author	Tueller, Stephen Lubke, Gitta
Copyright Year	2010
Description	Journal: Structural Equation Modeling: A Multidisciplinary Journal Structural Equation Mixture Models(SEMMs) are latent class models that permit the estimation of a structural equation model within each class. Fitting SEMMs is illustrated using data from one wave of the Notre Dame Longitudinal Study of Aging. Based on the model used in the illustration, SEMM parameter estimation and correct class assignment are investigated in a large scale simulation study. Design factors of the simulation study are (im)balanced class proportions, (im)balanced factor variances, sample size, and class separation. We compare the fit of models with correct and misspecified within-class structural relations. In addition, we investigate the potential to fit SEMMs with binary indicators. The structure of within-class distributions can be recovered under a wide variety of conditions, indicating the general potential and flexibility of SEMMs to test complex within-class models. Correct class assignment is limited.
Related Links	http://europepmc.org/articles/pmc2890304?pdf=render https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2890304/pdf
Ending Page	192
Page Count	28
Starting Page	165
ISSN	10705511
e-ISSN	15328007
DOI	10.1080/10705511003659318
Journal	Structural Equation Modeling: A Multidisciplinary Journal
Issue Number	2
Volume Number	17
Language	English
Publisher	Informa UK Limited
Publisher Date	2010-04-13
Access Restriction	Open
Subject Keyword	Journal: Structural Equation Modeling: A Multidisciplinary Journal Mathematical Social Sciences Structural Equation Correct Class Class Models Class Assignment
Content Type	Text
Subject	Sociology and Political Science Economics, Econometrics and Finance Decision Sciences Modeling and Simulation

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