Course Proforma: Structural Equation Modeling (SEM) with JAMOVI
1. Course Overview
Structural Equation Modeling (SEM) is a powerful statistical technique that allows researchers to examine complex relationships between variables, test theoretical frameworks, and validate measurement models. This course introduces PhD students, researchers, and academics to SEM using JAMOVI, a user-friendly software equipped with advanced SEM capabilities through its modules like lavaan. Participants will learn to design, estimate, and interpret SEM models to address their research questions rigorously and effectively.
2. Targeted Audience
- PhD students and researchers working on studies that require path analysis, factor analysis, or testing mediation and moderation effects.
- Master’s students preparing for thesis work involving advanced statistical methods.
- Academics and lecturers seeking to incorporate SEM into their research and teaching.
- Early-career researchers and professionals aiming to strengthen their statistical modeling skills for research or policy analysis.
3. Common Problems Faced
- Complexity of SEM Concepts: Many researchers struggle to understand the foundational concepts of SEM, such as latent variables and model fit.
- Software Intimidation: Existing SEM software can be expensive and difficult to navigate, creating a barrier to entry.
- Challenges in Model Validation: Difficulty in correctly specifying and validating SEM models often leads to invalid results.
- Inability to Interpret and Present Results: Researchers frequently encounter challenges in linking SEM outputs to their research hypotheses and effectively communicating findings.
4. Needs and Solutions
Needs Identified:
- A comprehensive understanding of SEM principles and practical applications.
- A user-friendly tool like JAMOVI to simplify SEM analysis.
- Guidance on interpreting SEM outputs and presenting results in research contexts.
Course Solutions:
- Learning Objectives:
a. Understand the key concepts and applications of SEM in research.
b. Develop proficiency in using JAMOVI and its modules for SEM analysis.
c. Learn to specify, estimate, and evaluate SEM models, including path analysis, CFA, mediation, and moderation.
d. Gain skills to interpret and present SEM results effectively in academic and professional settings. - Learning Outcomes:
a. Participants will confidently design and execute SEM analyses using JAMOVI.
b. Students will interpret SEM outputs and link findings to theoretical frameworks.
c. Attendees will improve the quality of their research by correctly validating and reporting SEM models.
d. Graduates will enhance their ability to produce high-impact publications and reports.
5. Course Content
Module 1: Introduction to Structural Equation Modeling
- Overview of SEM: Applications and benefits.
- Key SEM concepts: Latent variables, observed variables, and model specification.
- Understanding model fit indices: CFI, RMSEA, SRMR, and Chi-square.
Module 2: Getting Started with JAMOVI for SEM
- Exploring JAMOVI’s interface and SEM capabilities.
- Installing and using the lavaan module for SEM analysis.
- Importing and preparing datasets for SEM.
Module 3: Path Analysis and Regression Modeling
- Building and interpreting direct and indirect effects in path analysis.
- Conducting mediation and moderation analysis using SEM.
- Visualizing path diagrams and interpreting coefficients.
Module 4: Confirmatory Factor Analysis (CFA)
- Designing and testing measurement models.
- Evaluating construct validity: Convergent and discriminant validity.
- Modifying models for improved fit.
Module 5: Advanced SEM Techniques
- Structural models: Linking measurement and structural models.
- Multi-group SEM for testing group differences.
- Handling missing data and model comparison.
Module 6: Reporting and Presenting SEM Results
- Writing results sections for theses and publications.
- Creating and interpreting visual outputs: Path diagrams and fit tables.
- Addressing limitations and ensuring methodological rigor.
6. Pedagogical Approach
- Hands-On Training: Practical exercises with sample datasets to ensure skill acquisition.
- Interactive Sessions: Live demonstrations of SEM model building in JAMOVI.
- Customized Feedback: Individualized guidance on participants’ datasets and research questions.
- Post-Course Resources: Access to video tutorials, templates, and guides for future reference.
7. Benefits to Participants
- Gain clarity on SEM principles and their application to research.
- Learn to use JAMOVI as a cost-effective and accessible tool for SEM.
- Enhance research rigor through proper model specification, estimation, and validation.
- Improve confidence in publishing research and presenting findings using SEM.
8. Conclusion
This course provides a step-by-step guide to mastering Structural Equation Modeling using JAMOVI. Whether you are designing a theoretical model, testing mediation effects, or conducting factor analysis, this program offers everything you need to elevate your research. Join us to transform your data into impactful insights and become proficient in one of the most sought-after statistical techniques in academic and professional fields.
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