ONLINE An introduction to latent variable modelling (such as principal component or factor analyses) in R
This Advanced Quantitative Research Methods workshop is open to all ESRC and non-ESRC funded MA Social Research and PhD students within the WRDTP partner universities.
Latent variable modelling at its most basic involves taking original variables from data and transforming them in some way to give new variables with useful properties. Sometimes this can be used to create uncorrelated variables that can allow dimension reduction (like principal component analysis). Other times the new variables are chosen to best explain the relationships between original variables in our data and to represent underlying, unobservable constructs (e.g. intelligence or political opinion) as is the case with factor analysis. These methods will be introduced in general and then students will be given the chance to learn how to apply them to data in R using a variety of commands and packages. Some working knowledge of R is essential for this course (e.g. using basic commands, plotting, etc). If there is time, we may discuss some basic item response theory models as well.
Workshop organiser/ leader
Through her previous work with AQMeN, she was involved in statistical modelling for different social science application areas including housing and criminology. In addition to this she has been involved in modelling educational testing and forensics data as well as disease mapping. She has also presented extremely successful short courses in the past for social scientists on the topics of cluster analysis, social network analysis and multivariate modelling.
There are 15 places available at this AQM workshop
This training session will be delivered via Blackboard Collaborate. The link to this event will be sent to students who book on via the booking form below.
PLEASE NOTE: Our online training sessions will be recorded and will be available on the VIRE in an edited format for those students who cannot attend. If you wish to join this session but do not wish for your contributions to be included in the edited VIRE resource please indicate this on the booking form.