Practitioner’s Guide to Latent Class Analysis: Methodological Considerations and Common Pitfalls.

By P. Sinha, C. Calfee, Kevin Delucchi. Critical Care Medicine, 2020

852 citations recorded by the source corpus.

Latent Class Analysis (LCA) is a probabilistic modelling algorithm that allows clustering of data and statistical inference. There has been a recent upsurge in the application of LCA in the fields of critical care, respiratory medicine, and beyond. In this review, we present a brief overview of the principles behind LCA. Further, in a stepwise manner, we outline the key processes necessary to perform LCA including some of the challenges and pitfalls faced at each of these steps. The review provides a one-stop shop for investigators seeking to apply LCA to their data.

Subfields: Epidemiology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ec46ed6c2e09e62e108862c2a63bebb02d950c01