Exploratory Procedure for Component-Based Structural Equation Modeling for Simple Structure by Simultaneous Rotation

• Published in: Psychometrika 2024-06, Vol.89 (2), p.411-438
• Main Author: Yamashita, Naoto
• Format: Article
• Language: English
• Subjects: Algorithms; Assessment; Behavioral Science and Psychology; Computer Simulation; Factor Analysis; Factor Analysis, Statistical; Humanities; Humans; Latent Class Analysis; Law; Mathematical models; Models, Statistical; Psychology; Psychometrics; Psychometrics - methods; Rotation; Statistical Theory and Methods; Statistics for Social Sciences; Structural equation modeling; Structural Equation Models; Testing and Evaluation; Theory and Methods
• ISSN: 0033-3123; 1860-0980; 1860-0980
• DOI: 10.1007/s11336-023-09942-5

Generalized structured component analysis (GSCA) is a structural equation modeling (SEM) procedure that constructs components by weighted sums of observed variables and confirmatorily examines their regressional relationship. The research proposes an exploratory version of GSCA, called exploratory GSCA (EGSCA). EGSCA is analogous to exploratory SEM (ESEM) developed as an exploratory factor-based SEM procedure, which seeks the relationships between the observed variables and the components by orthogonal rotation of the parameter matrices. The indeterminacy of orthogonal rotation in GSCA is first shown as a theoretical support of the proposed method. The whole EGSCA procedure is then presented, together with a new rotational algorithm specialized to EGSCA, which aims at simultaneous simplification of all parameter matrices. Two numerical simulation studies revealed that EGSCA with the following rotation successfully recovered the true values of the parameter matrices and was superior to the existing GSCA procedure. EGSCA was applied to two real datasets, and the model suggested by the EGSCA’s result was shown to be better than the model proposed by previous research, which demonstrates the effectiveness of EGSCA in model exploration.