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Analysis of Multiple Dependent Variables$
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Patrick Dattalo

Print publication date: 2013

Print ISBN-13: 9780199773596

Published to Oxford Scholarship Online: May 2013

DOI: 10.1093/acprof:oso/9780199773596.001.0001

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Structural Equation Modeling

Structural Equation Modeling

Chapter:
(p.109) 5 Structural Equation Modeling
Source:
Analysis of Multiple Dependent Variables
Author(s):

Patrick Dattalo

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199773596.003.0005

This chapter discusses structural equation modeling (SEM), also referred to as causal modeling and covariance structure analysis, which is used to evaluate the consistency of substantive theories with empirical data. SEM is a hybrid model that integrates path analysis and factor analysis. SEM is related to factor analysis because it may be used to test hypothesized relationships between unmeasured or latent variables and observed or empirical indicators of latent variables. SEM is related to path analysis because it may be used to test hypothesized relationships between constructs. Thinking of SEM as a combination of factor analysis and path analysis ensures consideration of SEM's two primary components: the measurement model and the structural model.

Keywords:   SEM, causal modeling, covariance structure analysis, statistical analysis, factor analysis, path analysis, measurement model, structural model

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