Mixture Models: Latent Profile and Latent Class Analysis

By Daniel L. Oberski. 2016

536 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/d474fcaae5ea4b32fa4596086e5d805406ebf38d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Experimental and Cognitive Psychology

1. Michael Schneider
2. E. W. G. Moore
3. D. Hull
4. Sarah Ferguson
5. Jake McMullen

Citations in the corpus

• Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers (2020, background): “In LPA, observed variables are continuous, analogous to a gaussian model (Oberski, 2016).”
• Informative tools for characterizing individual differences in learning: Latent class, latent profile, and latent transition analysis (2017, background): “These models are more flexible, account for measurement error, and are able to handle longitudinal data (e.g., Magidson & Vermunt, 2002, 2004; Oberski, 2016; Vermunt, Tran, & Magidson, 2008).”