What are the advantages of SEM over OLS regression?
• Given the advantages of SEM over OLS regression, when would one ever want to use OLS regression? Jaccard and Wan (1996: 80) state that regression may be preferred to structural equation modeling when there are substantial departures from the SEM assumptions of multivariate normality of the indicators and/or small sample sizes, and when measurement error is less of a concern because the measures have high reliability. • Is SEM the same as MLE? Can SEM use other estimation methods than MLE? SEM is a family of methods for testing models. MLE (maximum likelihood estimation) is the default method of estimating structure (path) coefficients in SEM, but there are other methods, not all of which are offered by all model estimation packages: • OLS. Ordinary least squares (OLS). This is the common form of multiple regression, used in early, stand-alone path analysis programs. It makes estimates based on minimizing the sum of squared deviations of the linear estimates from the observed scores.
