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Abstract
The relationship between variables in structural equation modeling (SEM) forms a structural model. This structural model can be explained through structural equations, such as in regression analysis. This structural equation describes the prediction of the latent (exogenous) independent variable on the latent (endogenous) dependent variable. Researchers who use analysis with structural equation models need to know whether the model built with empirical data has a unique value or not so that the model can be estimated. If the model does not have a unique value, then the model cannot be identified (unidentified). The cause of a model is categorized as unidentified because the information contained in empirical data is not sufficient to produce a unique solution in calculating model estimation parameters. This literature review aims to describe the process of data analysis using SEM.
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