Structural equation modelling (SEM) is a century-old statistical method that witnessed progression over time. Initially, the model focused only on path analysis. However, with the growth in usage of SEM in social science, the factor analysis technique was integrated into it. Presently SEM is a powerful multivariate technique applicable in scientific investigations to evaluate and test the multivariate casual relationships. The challenge today is that research problems are of different kinds and there are multiple models. Therefore, it is essential to understand the basics before applying structural equation modelling in research.
Structural equation modeling (SEM) is a powerful multivariate technique used increasingly in scientific investigations for evaluating and testing the relationships between variables.
Structural equation modeling analysis being the multivariate statistical tool helps in determining the direct and indirect linkage between the variables.
Structural equation model is a statistical modeling technique. Structural equation model (SEM) tests estimate or establish relationships between variables. It is a multivariate statistical data analysis technique. SEM analyzes the structural relationships or to establish causal relationships between variables.
SEM is used to build structural links between measured variables and latent constructs. This article provides a detailed description of the SEM analysis procedures.