Structural Equation Modelling

Structure Equation Modelling (SEM) is a comprehensive statistical technique used for testing and estimating causal relationships (Kline, 2023). It is a multivariate approach that combines features of factor analysis and multiple regression, allowing for the examination of complex relationships among observed and latent variables. SEM is particularly useful when dealing with multiple variables and their interdependencies, making it a powerful tool in social sciences, psychology, marketing, and other fields. It enables researchers to test hypotheses about the relationships between observed variables and their underlying constructs (latent variables), as well as the direct and indirect effects among these constructs (Kline, 2023). SEM is a versatile and robust statistical method that allows researchers to explore and test complex relationships among variables, providing a comprehensive understanding of the underlying structure of a set of observed and unobserved variables (Kline, 2023).

Publication Details

Journal
Edge Hill University Research Information Repository (Edge Hill University)
Published
2025-07-30
Primary Topic
Psychometric Methodologies and Testing
Type
article
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article

Structural Equation Modelling

Edge Hill University Research Information Repository (Edge Hill University)
Psychometric Methodologies and Testing
article

Structural Equation Modelling

article en

Abstract

Structure Equation Modelling (SEM) is a comprehensive statistical technique used for testing and estimating causal relationships (Kline, 2023). It is a multivariate approach that combines features of factor analysis and multiple regression, allowing for the examination of complex relationships among observed and latent variables. SEM is particularly useful when dealing with multiple variables and their interdependencies, making it a powerful tool in social sciences, psychology, marketing, and other fields. It enables researchers to test hypotheses about the relationships between observed variables and their underlying constructs (latent variables), as well as the direct and indirect effects among these constructs (Kline, 2023). SEM is a versatile and robust statistical method that allows researchers to explore and test complex relationships among variables, providing a comprehensive understanding of the underlying structure of a set of observed and unobserved variables (Kline, 2023).

Edge Hill University Research Information Repository (Edge Hill University)
Reduced inequalities
Openalex Percentile: Top 40%
Psychometric Methodologies and Testing
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