Structural Equation Modelling (RSS555)

RSS555 Structural Equation Modelling introduces students to the principles and applications of Structural Equation Modelling (SEM), an advanced statistical technique widely used in psychology, social sciences, and organisational research. SEM integrates factor analysis and multiple regression, allowing researchers to test complex models involving latent variables, mediation, and moderation. Students will learn the theory underlying SEM, how to specify and evaluate measurement models, and how to interpret structural paths. Students will also learn to use statistical software (e.g., R and RStudio) to conduct the analyses. At the end of the course, students will be able to independently conduct the appropriate analyses to answer their research questions, interpret the output, and write up the results.

• Data preparation
• Review of regression fundamentals
• Review of psychometrics fundamentals
• Path models I: Mediation
• Path models II: Moderation
• Factor analysis
• Structural regression models I
• Structural regression models II
• Structural regression models III
• Structural regression models IV
• Advanced techniques I
• Best practices

• Assess how structural equation modelling can be applied in different research contexts
• Formulate research questions and a suitable framework for data analysis with given data sets
• Evaluate the statistical output
• Analyse data using statistical software
• Select the appropriate statistical techniques for different types of data and research
• designs, and to address different research questions
• Construct accurate models to test theories