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Introduction to Latent Class Analysis
14th February 2019 @ 8:00 am - 15th February 2019 @ 5:00 pm
|Organised by||The University of Manchester|
|Presenter||Dr. Alexandru Cernat|
|Date||14/02/2019 – 15/02/2019|
|Venue||Cathie Marsh Institute
Humanities Bridgeford street
University of Manchester
|Map||View in Google Maps (M13 9PL)|
|Contact||Claire Spencer, 0161 275 4579, [email protected]|
|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:
By the end of the course participants will:
Knowledge of basic categorical analysis: (marginal) probabilities, odds ratios, logistic regression.
Day 1 – introduction to LCA
Day 2 – applications of LCA
|Level||Intermediate (some prior knowledge)|
|Cost||For UK registered postgraduate students £30 per day
For staff at UK academic institutions, ESRC funded researchers and registered charity organisations £60 per day
For all other participants £220 per day
|Website and registration|
|Keywords||Latent class growth analysis, Latent Variable Models, Latent class analysis, Latent profile analysis, Latent trait analysis|
|Related publications and presentations||Latent class growth analysis
Latent Variable Models
Latent class analysis
Latent profile analysis
Latent trait analysis