An Introduction to Structural Equation Modeling
نویسندگان
چکیده
Abstract Structural equation modeling is a multivariate data analysis method for analyzing complex relationships among constructs and indicators. To estimate structural models, researchers generally draw on two methods: covariance-based SEM (CB-SEM) partial least squares (PLS-SEM). Whereas CB-SEM primarily used to confirm theories, PLS represents causal–predictive approach that emphasizes prediction in estimating whose structures are designed provide causal explanations. PLS-SEM also useful confirming measurement models. This chapter offers concise overview of PLS-SEM’s key characteristics discusses the main differences compared CB-SEM. The describes considerations when using highlights situations favor its use
منابع مشابه
An Introduction to Structural Equation Modeling
In this contribution the principles behind Structural Equation Modeling (SEM) are presented. SEM is used for assessing the quality of models that are proposed on the basis of theory and experience. This contribution has an introductory level.
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ژورنال
عنوان ژورنال: Classroom companion: business
سال: 2021
ISSN: ['2662-2874', '2662-2866']
DOI: https://doi.org/10.1007/978-3-030-80519-7_1