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



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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Use Videos and Resources to Practice JMP, JMP Pro, JMP Clinical and JMP Genomics.

1-hour live Mastering JMP webinars occur most Fridays from January through October. After each session, we hope you will use the video and resources shared by the presenting JMP Systems Engineers to practice what you saw.

Mastering JMP Videos are available here.