See how to:
- Understand the basics of SEM
- Confirmatory Factor Analysis (CFA) – a multivariate statistical procedure to test how well measured variables represent the number of constructs and confirm or reject a theory
- Path Analysis - an extension of the regression model built from the correlation matrix that compares two or more casual models and uses a diagram flow chart to model path and causation
- Structural Equation Modeling (SEM) – Multivariate statistical analysis technique that combines factor analysis with multiple regression analysis to analyze structural relationship between measured variables and latent constructs, estimating multiple and interrelated dependence in a single analysis
- Select models and handle measurement areas using an industrial case study
- Navigate the 3-panel SEM window (From List, To List, Diagram)
- Use SEM to see if there is any built-in error in your measurements
- Understand how to examine and compare restricted and independent model results
- Build multiple models iteratively and interpret requirement Rule Status before running models
- Locate and interpret model statistics and Report Warnings, and then modify or rerun models if necessary
- Use Local Data filter to filter by variable
- Save factor scores and apply latent variables to observed variables
- Use SEM to test a hypothesis using a sports case study
Note: Q&A included at time 36:43.
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