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Path Analysis and Latent Variables in SEM
( 30 Modules )

Module #1
Introduction to Structural Equation Modeling (SEM)
Overview of SEM, its applications, and significance
Module #2
Path Analysis:A Brief History and Overview
History, development, and basic concepts of Path Analysis
Module #3
Latent Variables:Definition, Types, and Importance
Concept of latent variables, types (e.g., reflective, formative), and their role in SEM
Module #4
Path Diagram Notation and Basics
Path diagram notation, symbols, and basic rules
Module #5
Path Coefficients and Standardization
Path coefficients, standardization, and interpretation
Module #6
Direct and Indirect Effects
Direct, indirect, and total effects in Path Analysis
Module #7
Mediation Analysis
Mediation models, types (e.g., full, partial), and estimation
Module #8
Moderation Analysis
Moderation models, types (e.g., simple, multiple), and estimation
Module #9
Introduction to Latent Variable Models
Basic concepts of Latent Variable Models (LVMs), including Confirmatory Factor Analysis (CFA)
Module #10
Latent Variable Models:Estimation and Identification
Estimation methods (e.g., ML, WLS), identification issues, and remedies
Module #11
Measurement Models
Measurement models, types (e.g., reflective, formative), and specification
Module #12
Structural Models
Structural models, types (e.g., recursive, non-recursive), and specification
Module #13
Model Fit Indices and Evaluation
Model fit indices (e.g., Chi-squared, RMSEA), evaluation, and interpretation
Module #14
Model Modification and Specification Search
Model modification, specification search, and cross-validation
Module #15
Common Methodological Issues and Solutions
Common methodological issues (e.g., common method variance, endogeneity) and solutions
Module #16
Advanced Topics in Latent Variable Models
Advanced topics (e.g., non-normality, categorical variables, MIMIC models)
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


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