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Direct linkHwang, 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
Maximum Likelihood Analysis of a Two-Level Nonlinear Structural Equation Model with Fixed Covariates
Lee, Sik-Yum; Song, Xin-Yuan – Journal of Educational and Behavioral Statistics, 2005
In this article, a maximum likelihood (ML) approach for analyzing a rather general two-level structural equation model is developed for hierarchically structured data that are very common in educational and/or behavioral research. The proposed two-level model can accommodate nonlinear causal relations among latent variables as well as effects…
Descriptors: Mathematics, Sampling, Structural Equation Models, Bayesian Statistics
