*연구과제명: Comparison of Component-Based Structural Equation Modeling Methods in Testing Component Interaction Effects
-연구 기관: McGill University, The Ohio State University, Sogang University (연구팀)
-저자: Zhiyuan Shen, Gyeongcheol Cho & Heungsun Hwang
Generalized structured component analysis (GSCA) and partial least squares path modeling (PLSPM) are statistical methods for component-based structural equation modeling, where constructs are repre sented as components or weighted sums of observed variables. While both methods employ different approaches to testing an interaction effect between components, their comparative performance in this context has not been systematically investigated. To address this gap, we conducted a simulation study to evaluate their relative performance across various experimental conditions. The results indi cate that GSCA’s approach consistently outperforms PLSPM’s in testing a component interaction effect under all examined conditions.
*연구과제명: Comparison of Component-Based Structural Equation Modeling Methods in Testing Component Interaction Effects
-연구 기관: McGill University, The Ohio State University, Sogang University (연구팀)
-저자: Zhiyuan Shen, Gyeongcheol Cho & Heungsun Hwang
Generalized structured component analysis (GSCA) and partial least squares path modeling (PLSPM) are statistical methods for component-based structural equation modeling, where constructs are repre sented as components or weighted sums of observed variables. While both methods employ different approaches to testing an interaction effect between components, their comparative performance in this context has not been systematically investigated. To address this gap, we conducted a simulation study to evaluate their relative performance across various experimental conditions. The results indi cate that GSCA’s approach consistently outperforms PLSPM’s in testing a component interaction effect under all examined conditions.