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Direct linkHwang, Heungsun; Suk, Hye Won; Lee, Jang-Han; Moskowitz, D. S.; Lim, Jooseop – Psychometrika, 2012
We propose a functional version of extended redundancy analysis that examines directional relationships among several sets of multivariate variables. As in extended redundancy analysis, the proposed method posits that a weighed composite of each set of exogenous variables influences a set of endogenous variables. It further considers endogenous…
Descriptors: Redundancy, Psychometrics, Computation, Least Squares Statistics
Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S. – Psychometrika, 2012
We propose a new method of structural equation modeling (SEM) for longitudinal and time series data, named Dynamic GSCA (Generalized Structured Component Analysis). The proposed method extends the original GSCA by incorporating a multivariate autoregressive model to account for the dynamic nature of data taken over time. Dynamic GSCA also…
Descriptors: Structural Equation Models, Longitudinal Studies, Data Analysis, Reliability
Hwang, Heungsun; Ho, Moon-Ho Ringo; Lee, Jonathan – Psychometrika, 2010
Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…
Descriptors: Monte Carlo Methods, Structural Equation Models, Interaction, Researchers
Hwang, Heungsun – Psychometrika, 2009
Generalized structured component analysis (GSCA) has been proposed as a component-based approach to structural equation modeling. In practice, GSCA may suffer from multi-collinearity, i.e., high correlations among exogenous variables. GSCA has yet no remedy for this problem. Thus, a regularized extension of GSCA is proposed that integrates a ridge…
Descriptors: Monte Carlo Methods, Structural Equation Models, Least Squares Statistics, Computation
Hwang, Heungsun; Desarbo, Wayne S.; Takane, Yoshio – Psychometrika, 2007
Generalized Structured Component Analysis (GSCA) was recently introduced by Hwang and Takane (2004) as a component-based approach to path analysis with latent variables. The parameters of GSCA are estimated by pooling data across respondents under the implicit assumption that they all come from a single, homogenous group. However, as has been…
Descriptors: Urban Areas, Path Analysis, Monte Carlo Methods, Drinking
Hwang, Heungsun; Takane, Yoshio – Psychometrika, 2004
We propose an alternative method to partial least squares for path analysis with components, called generalized structured component analysis. The proposed method replaces factors by exact linear combinations of observed variables. It employs a well-defined least squares criterion to estimate model parameters. As a result, the proposed method…
Descriptors: Path Analysis, Least Squares Statistics, Mathematics, Evaluation Methods
