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Structural Equation Modeling

Kayla Jordan D. Wayne Mitchell RStats Institute Missouri State University. Structural Equation Modeling. What is SEM?. Statistical technique useful for testing theoretical models Theory-driven Confirmatory. Types of Variables. Manifest or Observed Variable. Error. Endogenous.

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Structural Equation Modeling

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  1. Kayla Jordan D. Wayne Mitchell RStats Institute Missouri State University Structural Equation Modeling

  2. What is SEM? • Statistical technique useful for testing theoretical models • Theory-driven • Confirmatory

  3. Types of Variables Manifest or Observed Variable Error Endogenous Residual Latent Variable Exogenous Variable

  4. Types of Models Measurement Model Structural Model

  5. Degrees of Freedom • Knowns: n(n+1)/2 -> 8(9)/2 -> 36 • Unknowns: 5 factor loadings, 2 path coefficients, 8 error variances, 2 residuals -> 17 total unknowns • Degrees of Freedom: Knowns – Unknowns -> 19

  6. Estimates

  7. Factor Loadings Indicates all observed variables are measuring the latent variable. Values closer to one indicate that the observed variable is measuring latent better (e.g., H3 is a better item than H6)

  8. Confirmatory Factor Analysis

  9. Path Analysis

  10. Full Structural Model

  11. Multi-Trait, Multi-Method

  12. Fit Indices

  13. Model Comparisons • Need for Multiple Models • Chi-Square Difference • CFI Difference

  14. Assumptions • Sample Size • Normality • Outliers • Multicollinearity

  15. Programs

  16. Questions?Contact: kaylajordan91@gmail.com

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