Bayesian Hierarchical Modelling with multiple timepoints for patients as an outcome

Hi,

The sd=100 on the Normal seems very broad. But that depends on your data. The link to the CSV you added does not work, so it’s hard to tell.

In general, you can use pm.sample_prior_predictive to make predictions with the model before fitting it to the data. Your models prior predictions should be “realistic”.

cheers