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Jongerling, Joran; Hamaker, Ellen L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article shows that the mean and covariance structure of the predetermined autoregressive latent trajectory (ALT) model are very flexible. As a result, the shape of the modeled growth curve can be quite different from what one might expect at first glance. This is illustrated with several numerical examples that show that, for example, a…
Descriptors: Statistics, Structural Equation Models, Scores, Predictor Variables
Equivalence and Differences between Structural Equation Modeling and State-Space Modeling Techniques
Chow, Sy-Miin; Ho, Moon-ho R.; Hamaker, Ellen L.; Dolan, Conor V. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
State-space modeling techniques have been compared to structural equation modeling (SEM) techniques in various contexts but their unique strengths have often been overshadowed by their similarities to SEM. In this article, we provide a comprehensive discussion of these 2 approaches' similarities and differences through analytic comparisons and…
Descriptors: Structural Equation Models, Differences, Statistical Analysis, Models
Zhang, Zhiyong; Hamaker, Ellen L.; Nesselroade, John R. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Four methods for estimating a dynamic factor model, the direct autoregressive factor score (DAFS) model, are evaluated and compared. The first method estimates the DAFS model using a Kalman filter algorithm based on its state space model representation. The second one employs the maximum likelihood estimation method based on the construction of a…
Descriptors: Structural Equation Models, Simulation, Computer Software, Least Squares Statistics