SEM in R: Structural Equation Modeling

Date:

14/01/2015 - 16/01/2015

Organised by:

University of Cambridge Psychometrics Centre

Presenter:

DR Luning Sun

Level:

Intermediate (some prior knowledge)

Contact:

Aiden Loe, 01223769485, bsl28@cam.ac.uk

Map:

View in Google Maps  (CB2 3EB)

Venue:

Psychology Department, University of Cambridge, Downing Street, Cambridge

Description:

This course is an introduction to Structural Equation Modelling (SEM) using R, the popular open-source statistical software environment for advanced statistical analysis and modelling. The 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 visualization tool for your data analysis. You will be learning the following topics in this course:  

  • Introduction to R and R studio
  • Graphical representations of data points and latent trait models.
  • Basic concepts of factor analysis (EFA / CFA / Categorical CFA)
  • Basic concepts of latent trait analysis (SEM)
  • Application of mediation & moderation techniques in Lavaan package

Participants should bring their laptop computers with them. Participants bringing their own laptop should:

  • Ensure to have installed the latest version of R from http://cran.r-project.org/
  • Download and install RStudio from http://www.rstudio.com/ide/download/
  • Download and install the lavaan package within R.
  • Download and install the ggplot2 package within R. 

Cost:

3 days: Business: £600, Academics: £400, Students: £300

2 days: Business: £450, Academics: £300, Students: £220

Website and registration:

Region:

East of England

Keywords:

Latent trait analysis, Principal components analysis, Factor analysis, Confirmatory factor analysis, Structural equation models, R

Related publications and presentations:

Latent trait analysis
Principal components analysis
Factor analysis
Confirmatory factor analysis
Structural equation models

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