A variety of phenomena examined in education can be described using categorical latent models, which help identify groups of individuals who have a series of characteristics in common. Usually, data are too complex to identify and describe groups through inspection alone; therefore, multivariate classification procedures such as latent class analysis (LCA) should be employed. LCA refers to a group of multivariate classification procedures used to identify subgroups of individuals who have several characteristics in common [1]. The following article provides a general description of LCA. It describes the latent class model and explains the steps involved in latent class modeling. Finally, the article includes an empirical application of LCA with binary indicators using the Mplus statistical software.

Published in: London International Conference on Education (LICE-2020)

• Date of Conference: 23-25 November 2020
• DOI: 10.2053/LICE.2020.0028
• ISBN: 978-1-913572-22-8
• Conference Location: London, UK