Uploaded April 2026 | Updated September 2026, 2 weeks ago
June 4, 2025
This workshop provides a brief introduction to LCA/LPA models and how to implement them using Stata. Latent variables are a useful tool for modeling hypothetical constructs such as intelligence, ability, depression, and anxiety. Models for categorical latent variables are often called Latent Class Analysis (LCA) or Latent Profile Analysis (LPA). The levels of a categorical latent variable represent groups in the population. LCA is characterized by discrete response variables while LPA is characterized by continuous response variables.
June 4, 2025
This workshop provides a brief introduction to LCA/LPA models and how to implement them using Stata. Latent variables are a useful tool for modeling hypothetical constructs such as intelligence, ability, depression, and anxiety. Models for categorical latent variables are often called Latent Class Analysis (LCA) or Latent Profile Analysis (LPA). The levels of a categorical latent variable represent groups in the population. LCA is characterized by discrete response variables while LPA is characterized by continuous response variables.
