Multivariate Data Analysis in R for Research Scholars

Dive into the world of data analysis and gain practical skills in powerful statistical techniques! This course provides a comprehensive guide to multivariate statistical techniques, focusing on logistic regression, Structural Equation Modeling (SEM), and Confirmatory Factor Analysis (CFA), all implemented in R Studio using the lavaan library.

Here's what you'll learn:

• Structural Equation Modeling (SEM): Master SEM, a powerful technique for testing complex relationships between variables. We'll cover higher-order constructs, mediation, and latent variables. Understand how SEM combines Confirmatory Factor Analysis (CFA) and Linear Regression to model intricate data structures. Learn to navigate the complexities of hierarchical component models and mediation/moderation approaches, presented in an accessible way.
• Confirmatory Factor Analysis (CFA): Gain a deep understanding of CFA – a crucial method for validating questionnaires. We'll explore fundamental concepts, key terms, and essential metrics like Composite Reliability, Discriminant Validity, and Average Variance Extracted (AVE). Mathematical equations are explained to clarify the relationship between factors and observed variables.
• Exploratory Factor Analysis (EFA): Learn to perform EFA and effectively interpret the results for clear documentation in research reports and theses. Prerequisites are reviewed to ensure a solid foundation.
• Data Analysis Workflow: All sessions are designed with the researcher in mind, starting from the point where you've collected primary data through a questionnaire.
• Logistic Regression: Explore logistic regression, a supervised machine learning technique, from basic principles to practical implementation and result interpretation. Learn to assess the effectiveness of your logistic regression model.

This course is specifically designed for research scholars and research supervisors seeking to implement SEM, EFA, and CFA in R. While we won't delve into every statistical detail, you'll gain sufficient knowledge to confidently document your research findings and enhance your thesis. Develop your skills in statistical modeling, data validation, and research reporting!