Structural Equation Modeling: Difference between revisions
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SEM is similar, but more powerful than [[Regression Analysis| Regression Analyses]]. | SEM is similar, but more powerful than [[Regression Analysis|Regression Analyses]]. | ||
SEM examines linear causal relationships among variables, while simultaneously accounting for measurement error. | SEM examines linear causal relationships among variables, while simultaneously accounting for measurement error. | ||
Revision as of 13:44, 9 January 2022
Structural Equation Modeling (SEM) is a set of statistical techniques used to measure and analyze the relationships of observed and latent variables.
SEM is similar, but more powerful than Regression Analyses.
SEM examines linear causal relationships among variables, while simultaneously accounting for measurement error.