Mediation and Moderation Analysis Using R

This one-day intermediate-level course introduces the concepts and techniques of moderation and mediation analysis using R, with a focus on social science applications. Participants will learn how to test for interaction effects (moderation) using regression models, conduct mediation analysis using structural equation modelling and combine both approaches to explore mediated moderation. Emphasis is placed on interpretation, visualization, and reproducible R workflows using real-world data examples.

The course covers: 

• A brief refresher on linear regression in R
• Moderation analysis using interaction terms in regression
• Probing and visualizing interaction effects
• Mediation analysis using path models
• Estimating indirect effects  
• Mediated moderation  
• Applied examples in social sciences
• Practical coding sessions using real datasets in R

By the end of the course participants will:

• Understand the conceptual foundations of moderation and mediation
• Conduct moderation analysis using interaction terms in R
• Interpret and visualize interaction effects  
• Specify and estimate mediation models using path analysis
• Test indirect effects and interpret mediation results
• Use SEM to explore differences in mediation across groups
• Apply techniques to real-world social science datasets

Course format  

This course will be delivered online on the 10th October 2025 from 9:00 am to 4:00 pm with lunch break from 12:00 pm to 1:00 pm. The day will be divided into two parts (morning and afternoon). The first part will cover moderation, and the second part will cover mediation. Each part will be divided in a lecture, followed by a hands on practical and then going through the solution as a group.
 
The course leader 

The course is Led by Dr Alexandru Cernat, a Professor at the University of Manchester, specialising in collecting and analysing longitudinal data. Over the past decade, he has published over 50 papers and book chapters using advanced statistical models to investigate how people and societies change. His main focus in on data quality and how to estimate it using latent variable modelling. 
Dr Alexandru Cernat is also the founder of longitudinalanalysis.com, a platform developed to help researchers and analysts learn how to collect, clean, and analyse longitudinal data.
 
Pre-requisites 
The course includes hands-on computer workshops. Participants will use the R programming language. 
All software is free and open source. Participants should have R and RStudio installed prior to the course (ideally the latest versions).  

Participants should be familiar with:

• Basic R usage (e.g., using lm(), loading data, basic plots)
• Multiple regression and interpreting coefficients

Recommended reading:  

• MacKinnon, D. P., Fairchild, A. J., & Fritz, M. S. (2007). Mediation Analysis. Annual Review of Psychology, 58(1), 593–614. LINK
• Spiller, S. A., Fitzsimons, G. J., LynchJR., J. G., & Mcclelland, G. H. (2013). Spotlights, Floodlights, and the Magic Number Zero: Simple Effects Tests in Moderated Regression. Journal of Marketing Research, 50(2), 277–288. LINK 

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If you have not previously created an account for the Online Store, you will need to create an account to make a booking.