Mediation and Moderation Analysis Using R

Description:

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, visualisation, 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 visualising 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 visualise 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 is 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

Cost:

The fee is £60 for students / £150 for staff working for academic institutions, Research Councils and other recognised research institutions, registered charity organisations and the public sector / £350 for all other participants. In the event of cancellation by the delegate, a full refund of the course fee is available up to two weeks prior to the course. NO refunds are available after this date. If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of its cancellation of a course, including but not limited to any travel or accommodation costs. The University of Southampton’s Online Store T&Cs also continue to apply.

Website and registration:

Register for this course

Region:

North West

Keywords:

Quantitative Data Handling and Data Analysis, Mediation, Moderation, Statistical interactions, Structural equation modelling, regression analysis, indirect effects

Related publications and presentations from our eprints archive:

Quantitative Data Handling and Data Analysis

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