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Labo-Lacourse / stepmix

A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods.
https://stepmix.readthedocs.io/en/latest/index.html
MIT License
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Minimal Response Z-test Example #58

Open sachaMorin opened 6 months ago

sachaMorin commented 6 months ago

We have this in scripts/run_real_example.py but it includes a lot of boilerplate to reproduce all the tables from the paper. I suggest we design a simpler example (e.g., with only 3-step BCH) and include it in the notebooks.

sachaMorin commented 6 months ago

@ericlacourse @FelixLaliberte I think we discussed this already and it has been requested by users a few times. I don't have cycles to take care of this these days, but I'm happy to share access to the notebooks