A multiple regression model could be conceptualized using Structural Equation Model path diagrams. That’s the simplest SEM you can create, but its real power lies in expanding on that regression model. Here I will discuss four types of structural equation models.
In most regression models, there is one response variable and one or more predictors. From the model’s point of view, it doesn’t matter if those predictors are there to predict, to moderate, to explain, or to control. All that matters is that they’re all Xs, on the right side of the equation.
What are goodness of fit statistics? Is the definition the same for all types of statistical model? Do we run the same tests for all types of statistic model?
One important step in creating scales is making sure the scale measures the latent construct equally well and the same way for different groups of individuals.
This score is an estimate of the value of the latent construct (factor) the scale is measuring for each subject. In fact, calculating this score is the final step of running a Confirmatory Factor Analysis.