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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
First-Order and Higher-Order Factors of Creative Social Intelligence within Guilford's Structure-of-Intellect Model: A Reanalysis of a Guilford Data Base.
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Chen Shyuefee, Agnes; Michael, William B. – Educational and Psychological Measurement, 1993
Confirmatory maximum likelihood factor analysis determined how accurately each of several hypothesized combinations of first-order and higher-order factors reflecting creativity in the social intelligence of 192 high school students described the covariation in selected submatrixes from the total correlation matrix originally analyzed. Results…
Descriptors: Correlation, Creativity, Factor Structure, High School Students