Latent Variable Models for Social Research (online)
Date:
14/09/2022
Organised by:
The University of Edinburgh
Presenter:
Dr Chris Playford, Quantitative Sociologist at the University of Exeter
Level:
Intermediate (some prior knowledge)
Contact:
Laura Marshall
L.marshall@ed.ac.uk
Working week Monday - Thursday
Venue: Online
Description:
Latent variable models relate a set of observed (or manifest) variables to a set of latent (or unmeasured) variables. In practice, this entails the use of models to summarise the relationship between a series of highly associated variables. It will be demonstrated that these models are specific examples of a wider family of measurement models.
This one-day course will showcase latent variable models through the application of these models to social science data. Particular emphasis will be given to estimation and interpretation of latent class models in Stata.
It is most suited to empirical social science researchers with knowledge of statistical data analysis methods.
The participants will be invited to use their own computers in some of the exercises. These will be conducted using Stata.
Course Timings: 10:00 - 16:00
Cost:
• £30 per day for UK/EU registered students • £60 per day for staff at UK/EU academic institutions, UK/EU Research Councils researchers, UK/EU public sector staff and staff at UK/EU registered charity organisations and recognised UK/EU research institutions. • £100per day for all other participants All fees include event materials, lunch, morning and afternoon tea. They do not include travel and accommodation costs. Cancellation Policy: Please be reminded that you will be charged the full registration fee if you cancel your place within 4 weeks before the training delivery date or you fail to attend. If you are able to fill the place on the course you are cancelling then the cancellation charge will not apply.
Website and registration:
Region:
Scotland
Keywords:
Latent Variable Models, Stata, Latent variable models' Generalized linear model (GLM), Factor Analysis, Latent Class Models, Latent Trait Models, Stata
Related publications and presentations: