Training and Events
Introduction to Latent Class Analysis
|NCRM, University of Southampton|
Dr Alexandru Cernat
03/02/2020 - 04/02/2020
University of Southampton, Building 39, Highfield, Southampton, Hants
View in Google Maps (SO17 1BJ)
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:
By the end of the course participants will:
The course is aimed at people from all disciplines and types of institutions that want to learn about latent class analysis or, more generally, about latent variable modelling.
Knowledge of basic categorical analysis: (marginal) probabilities, odds ratios, logistic regression and of linear regression.
For an introduction to Latent Class Analysis:
Collins, L. M., & Lanza, S. T. (2010). Latent Class and Latent Transition Analysis: with Applications in the Social, Behavioral, and Health Sciences (1 edition). Hoboken, N.J: Wiley-Blackwell.
Applications of Latent Class Analysis:
Hagenaars, J., & McCutcheon, A. (Eds.). (2009). Applied Latent Class Analysis (1 edition). Cambridge; New York: Cambridge University Press.
Reading on categorical data analysis:
Agresti, A. (2007). An Introduction to Categorical Data Analysis (2nd Revised edition edition). Hoboken, NJ: John Wiley & Sons.
Intermediate (some prior knowledge)
The fee per teaching day is:
Website and registration
Latent Variable Models, Latent class analysis, Latent GOLD , Classification , Categorical Data Analysis , Longitudinal Analysis , Multi-group Analysis
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