Introduction to Latent Class Analysis
Date:
15/09/2016 - 16/09/2016
Organised by:
NCRM, University of Southampton
Presenter:
Dr Alexandru Cernat
Level:
Entry (no or almost no prior knowledge)
Contact:
Jacqui Thorp
Training and Capacity Building Co-ordinator
NCRM, University of Southampton
Tel: 023 80594069
Email: jmh6@soton.ac.uk
Map:
View in Google Maps (BT7 1LQ)
Venue:
Queens University, McClay Library, College Park Avenue, Belfast
Description:
Latent Class Analysis (LCA) is a branch of the more General Latent Variable Modelling approach. It is typically used to classify subjects (such as individuals or countries) in groups that represent underlying patterns from the data. In addition to this application LCA provides a flexible framework that can be used in a wide range of contexts: in longitudinal studies (e.g., mixture latent growth models, hidden Markov chains), in evaluation of data quality (e.g., extreme response style, cross-cultural equivalence), non-parametric multilevel models, joint modelling for dealing with missing data.
In this course you will receive an introduction to the essential topics of LCA such as: what is LCA, how to run models, how to choose between alternative models, how to classify observations, how to evaluate and predict classifications. You will also apply this knowledge to a number of more advanced models that look at the relationship between latent class variables and at longitudinal data.
The course covers:
- Refresher of basic concepts in categorical analysis: (marginal) probability, odds ratios, logistic regression;
- Basic concepts and assumptions of latent class analysis;
- Introduction to Latent GOLD software;
- Model fit evaluation: global, local and substantive evaluation;
- Classification of cases;
- Apply these concepts to a number of models looking at: predicting class membership, relationships between latent classes, hidden Markov chains.
By the end of the course participants will:
- Know what is Latent Class Analysis;
- Be able to estimate and interpret results from Latent Class Analysis;
- Be able to choose between alternative Latent Class Models;
- Understand latent class classification and how to predict it;
- Be able to investigate the relationship between latent class variables.
A knowledge of basic categorical analysis: (marginal) probabilities, odds ratios, logistic regression is advised.
Cost:
The fee per teaching day is:
• £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.
• £220 per day for all other participants
All fees include event materials, lunch, morning and afternoon tea. They do not include travel and accommodation costs.
Website and registration:
Region:
Northern Ireland
Keywords:
Latent Variable Models, Latent class analysis, Latent GOLD , Classification , Categorical Data Analysis
Related publications and presentations from our eprints archive:
Latent Variable Models
Latent class analysis