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Right now model.plot() essentially makes predictions using it's own internal data. Predict does the same, but just using population level parameters and R's predict() function which conveniently can handle rfx scaling.
Refactor so that predict can take in new data, or use it's own data (i.e. when it's called via plot). Also add flag that it can make group level predictions using group level parameter fits.
The text was updated successfully, but these errors were encountered:
This doesnt actually make sense because plot is making marginal predictions not full predictions given all fitted coefficients. Makes sense to keep them separate.
Right now
model.plot()
essentially makes predictions using it's own internal data. Predict does the same, but just using population level parameters and R'spredict()
function which conveniently can handle rfx scaling.Refactor so that
predict
can take in new data, or use it's own data (i.e. when it's called via plot). Also add flag that it can make group level predictions using group level parameter fits.The text was updated successfully, but these errors were encountered: