Using Structural Equation Models to Uncover Relationships between Observed and Latent Variables

Application Area:
Statistics, Predictive Modeling and Data Mining

Learn about Structural Equation Models, when they might be useful, and how to create them to specify and test hypothesized relationships among observed and unobserved variables.  See how JMP Pro starts by modeling means and variances for all variables, lets you see multiple views of the model while it is being built and provides model details that can alert you to model weaknesses prior to running the model. Learn how to compare fitted models to baseline unrestricted and baseline independence models.

This webinar covers: Confirmatory Factor Analysis, Structural Regression, Latent Growth Curves, Conditional Latent Growth Curves and model comparison.

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