Week 9

SEM

Before Class

Articles

McCoach, D. B., & Cintron, D. (2022). Introduction to Modern Modelling Methods (1st edition). SAGE Publications Ltd.

Chapters 4 and 5

  • What is the purpose of SEM and how does it differ from other types of statistical models?

  • What are the key components of an SEM model, including latent variables, observed variables, and paths between variables?

  • How do you specify an SEM model, including selecting the appropriate measurement model and structural model?

  • How do you evaluate the fit (goodness) of an SEM model and what are some common fit indices used in SEM?

  • How do you interpret the results of a SEM analysis, including the path coefficients and factor loadings?

  • What are some common assumptions of SEM and how can you assess whether these assumptions are met?

  • How do you handle missing data in SEM and what are the implications of missing data for SEM analysis?

  • What are some common challenges and limitations of SEM and how can they be addressed?

  • What are the best practices for reporting SEM results and how can you communicate your findings effectively?

Videos

  • SEM basics
  • SEM basics