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Generalized Structured Component Analysis (GSCA) is a statistical technique used for modeling complex relationships among latent variables and observed indicators in a structured framework. It extends traditional component analysis methods by allowing for the incorporation of both reflective and formative measurement models. GSCA is particularly useful in fields like Social Sciences and marketing, where it helps in understanding the underlying structures and interactions in data while addressing issues like measurement error. This method enhances the interpretability and robustness of results derived from latent variable models.

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