Comments (1)
I.e. the following scheme: For multiple estimation based on the same fixed effects pair, e.g. a formula "Y1 + Y2 ~ sw(X1, X2) | X3 + X4",
- get the formula dict {"X3+X4": [ ["Y1 ~ X1"], ["Y1 ~ X2"], ["Y2 ~ X1"], ["Y2 ~ X2"]] }.
- get the variable dict {"X3+X4": ["Y1", "Y2", "X1", "X2"]}
- for the first formula "Y1 ~ X1", create the model matrix, drop NAs, get NA index, demean
- iterate for all formulas. before each iteration, check if variable combination in formula has already been demeand at NA combination
The status quo creates the model matrix after demeaning (which will not work with i.e. interacted variables) and brute force demeans all formulas individually.
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