|Organised by||The Psychometrics Centre, University of Cambridge|
|Presenter||Dr Lunintg Sun|
|Date||28/08/2018 – 31/08/2018|
|Venue||Cambridge Judge Business School
|Map||View in Google Maps (CB2 1AG)|
|Description||This course offers an introduction to Structural Equation Modelling (SEM) using R, the popular open-source software for statistical computing and graphics. It 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 be learning 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 attend Day 1, which is an introduction to the R software. 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.
Participants should bring their laptop computers with them, and have installed the latest version of R from https://www.r-project.org/and RStudio from http://www.rstudio.com/ide/download/ before arrival.
|Level||Entry (no or almost no prior knowledge)|
|Cost||4-days (Tues to Fri)
Business: £800 + 20% VAT
Academic: £600 + 20% VAT
Students: £500 + 20% VAT
3 days (Wed to Fri)
|Website and registration||
|Region||East of England|
|Keywords||Graphical modelling, Latent trait analysis, Factor analysis, Confirmatory factor analysis, Structural equation models, R, Multiple Group Analysis , Measurement Invariance|
|Related publications and presentations||Graphical modelling
Latent trait analysis
Confirmatory factor analysis
Structural equation models
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