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Structural Equation Modeling:…2
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State-Space Modeling of Dynamic Psychological Processes via the Kalman Smoother Algorithm: Rationale, Finite Sample Properties, and Applications
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Song, Hairong; Ferrer, Emilio – Structural Equation Modeling: A Multidisciplinary Journal, 2009
This article presents a state-space modeling (SSM) technique for fitting process factor analysis models directly to raw data. The Kalman smoother via the expectation-maximization algorithm to obtain maximum likelihood parameter estimates is used. To examine the finite sample properties of the estimates in SSM when common factors are involved, a…
Descriptors: Factor Analysis, Computation, Mathematics, Maximum Likelihood Statistics
A Bayesian Approach for Analyzing Hierarchical Data with Missing Outcomes through Structural Equation Models
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Song, Xin-Yuan; Lee, Sik-Yum – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Structural equation models are widely appreciated in behavioral, social, and psychological research to model relations between latent constructs and manifest variables, and to control for measurement errors. Most applications of structural equation models are based on fully observed data that are independently distributed. However, hierarchical…
Descriptors: Psychological Studies, Life Satisfaction, Job Satisfaction, Structural Equation Models