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I'd like to model a data set using Latent Class Analysis (LCA) using Python. I've found the Factor Analysis class in sklearn, but I'm not confident that this class is equivalent to LCA.
Does a package or class for LCA exist in Python?
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The standard procedure for conducting LCA is to conduct a sequence of models, starting with a one-class model and then specifying models with one additional class at a time. Researchers then compare the models based on statistical and substantive criteria.
Latent Class Analysis (LCA) is a statistical method for identifying unmeasured class membership among subjects using categorical and/or continuous observed variables. For example, you may wish to categorize people based on their drinking behaviors (observations) into different types of drinkers (latent classes).
There are seven approaches to choosing the number of classes: cross-validation, information criteria, statistical tests, extent of association with other data, entropy, replicability, no small classes, and domain-usefulness. Try your own Latent Class Analysis!
Latent profile analysis (LPA) is a categorical latent variable approach that focuses on identifying latent subpopulations within a population based on a certain set of variables.
At the moment, there is no package that provides LCA support in python. There are, however, many packages using different algorithms to perform LCA in R, for example (see the CRAN directory for more details):
Although not the same, there is a hierarchical clustering implementation in sklearn, you could check if that suits your needs.
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