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Savalei, Victoria – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Normal theory maximum likelihood (ML) is by far the most popular estimation and testing method used in structural equation modeling (SEM), and it is the default in most SEM programs. Even though this approach assumes multivariate normality of the data, its use can be justified on the grounds that it is fairly robust to the violations of the…
Descriptors: Structural Equation Models, Testing, Factor Analysis, Maximum Likelihood Statistics
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Asparouhov, Tihomir; Muthen, Bengt – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Exploratory factor analysis (EFA) is a frequently used multivariate analysis technique in statistics. Jennrich and Sampson (1966) solved a significant EFA factor loading matrix rotation problem by deriving the direct Quartimin rotation. Jennrich was also the first to develop standard errors for rotated solutions, although these have still not made…
Descriptors: Structural Equation Models, Testing, Factor Analysis, Research Methodology