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...

We propose an improved method for generalized constrained canonical correlation analysis (GCCANO). In GCCANO, data matrices are first decomposed into several submatrices according to some external information on rows and columns of the data matrices. Decomposed matrices are then subjected to...

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...