Module #17 Path Analysis and Latent Variables in Practice Real-world applications, case studies, and best practices
Module #18 Software for Path Analysis and Latent Variable Models Overview of popular software (e.g., AMOS, Mplus, lavaan) and hands-on practice
Module #19 Troubleshooting Common Errors and Issues Common errors, issues, and troubleshooting strategies
Module #20 Interpreting and Reporting Results Interpreting and reporting results, including visualizations and tables
Module #21 Path Analysis and Latent Variables in Different Disciplines Applications in various fields (e.g., psychology, marketing, education)
Module #22 Critique and Refinement of Path Analysis and Latent Variable Models Critique, refinement, and extensions of Path Analysis and Latent Variable Models
Module #23 Longitudinal and Multilevel Analysis Longitudinal and multilevel analysis in Path Analysis and Latent Variable Models
Module #24 Bayesian Approaches to Path Analysis and Latent Variable Models Bayesian approaches, Markov Chain Monte Carlo (MCMC), and Bayesian estimation
Module #25 Path Analysis and Latent Variables in Big Data Handling big data, data preprocessing, and scalability issues
Module #26 Advanced Topics in SEM and Future Directions Advanced topics, recent developments, and future directions in SEM
Module #27 SEM Software Packages and Advanced Features Advanced features and capabilities of popular SEM software packages
Module #28 Case Studies and Group Projects Guided case studies and group projects, including data analysis and presentation
Module #29 Best Practices and Tips for SEM Applications Best practices, common pitfalls, and tips for successful SEM applications
Module #30 Course Wrap-Up & Conclusion Planning next steps in Path Analysis and Latent Variables in SEM career
