(Live Online) SEM in R Workshop (4 or 5 days) July 2027

Structural Equation Modelling in R: 4- or 5-Day Live Online Course 

Dates: 5 - 9 July 2027

Location: Online Course (via Zoom) *Troubleshooting Info

Tutors: Dr Luning Sun and Dr Chia-Wen Chen

This live online course (administered via Zoom) offers an engaging introduction to Structural Equation Modelling (SEM) using R, the popular open-source software for statistical computing and graphics. The course will run over 5 consecutive days and will combine synchronous live lectures, individual exercises, group discussions and small group supervisions to simulate a live classroom environment. High contact with our expert instructors and interactive group work will further contribute to recreating the classic Cambridge experience in an online setting.

This course will present the lavaan package, rapidly becoming the tool of preference for SEM in R. Participants will actively work through practical examples to gain first-hand experience in the application of factor analysis and other more advanced latent trait models. You will learn the following topics in this course:  

• Introduction to R and data analysis
• Basic concepts of factor analysis (EFA/CFA/Categorical CFA)
• Basic and advanced Structural Equation Models (SEM)
• Application of mediation & moderation techniques
• Multi-level modelling
• Latent growth curve modelling
• Multiple-group analysis and evaluation of continuous and categorical data measurement invariance, as well as longitudinal measurement invariance

You don’t need to know R to follow the course. However, if you are not familiar with R, you will need to choose the 5 day option, which includes an introduction to the R software on Day 1. On completion, participants should have a good knowledge of the topics covered and have acquired an independent use of R and latent trait analysis.

We believe in active learning and developing practical skills. Thus, the necessary theoretical introduction will be illustrated with practical examples and we will be working with real data. No prior knowledge about SEM is assumed. The pace of teaching is adjusted to suit the level of the participants. Teaching will be in small groups so that delegates can make the most of the teaching.

Certification

All participants will receive a digital copy of their Certificate of Attendance, signed by the course instructors and displaying the University of Cambridge Psychometrics Centre logo.

Click to pay by card or request an invoice (Price per delegate inc. VAT):

5 days (Monday AM to Friday PM)

Register as an individual:

Concession: £834 | Early bird: £954

Register through an organisation:

Concession: £834 | Early bird: £954

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4 days (Tuesday AM to Friday PM)

Register as an individual:

Concession: £714 | Early bird: £774

Register through an organisation:

Concession: £714 | Early bird: £774

Note:

• Concession rate applies only for students in full-time study or academics employed at Universities and registered charities. Please get in touch to discuss other circumstances.

Before attending:

1. Install the Zoom Client for Meetings. You will receive an invite to the Zoom sessions from instructors after course registration. The native client works better than the browser plug-in.

2. Install the latest version of R from https://www.r-project.org/

3. Install the latest version of RStudio from http://www.rstudio.com/ide/download/ 

4. Make sure you have a stable internet connection and that your microphone, headphones and webcam are all working in Zoom. You will need to use these throughout the course to communicate with instructors and other delegates.

5. You can expect to receive a Zoom link one week before the course

Teaching plan:

Each day will require around 6 hours of contact time from each delegate, plus breaks. Sessions are varied and incorporate lectures, individual exercises, group work and small group supervision, split between the morning and afternoon sessions.

Morning Session (09.30-10.50, 11.10-12.30)

Afternoon Session (14.00-15.20, 15.40-17.00)

Day 1

• Introduction to R
• Data analysis in R

Day 2

• Path analysis
• Mediation and moderation analysis
• Multilevel modelling

Day 3

• Exploratory Factor Analysis
• Confirmatory Factor Analysis

Day 4

• Full SEM
• Measurement invariance across groups (multiple-group CFA)

Day 5

• Latent growth curve modelling
• Measurement invariance within-person (longitudinal measurement invariance)