Training and Events
3 or 4.5 Day Live Online Course: Structural Equation Modelling in R
|University of Cambridge|
Dr Luning Sun, Dr Aiden Loe
24/08/2020 - 28/08/2020
The Psychometrics Centre, Cambridge Judge Business School, Trumpington Street
View in Google Maps (CB2 1AG)
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 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. We will also introduce ggplot2, a simple R package for data visualisation. You will learn the following topics in this course:
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 4.5 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.
More information can be found here:
Entry (no or almost no prior knowledge)
£695, £795 or £945
Website and registration
East of England
Descriptive Statistics, Latent Variable Models, Structural Equation Modelling, R, Exploratory Factor Analysis
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