Currently, it is only possible to control for multiple testing for hypothesis of the same parameter, against the same null.
from pyfixest.estimation import feols
from pyfixest.utils import get_data
from pyfixest.multcomp import rwolf
data = get_data().dropna()
fit = feols("Y ~ Y2 + X1 + X2", data=data)
rwolf(fit.to_list(), "X1", reps=9999, seed=123)
E.g. for a set of regression models $s = 1, ..., S$, we can only test that $\beta{ks} = 0$ for a parameter k. In the example above, the parameter to be tested, "X1", needs to be fixed across models. It is not possible to e.g. test more complex hypotheses, as e.g. $\beta{1,1} = 0$, $\beta_{1,2} = 0$, etc.
To Do
Define an API that allows users to test more complex hypotheses via bonferroni() and rwolf(). We can draw some inspiration from the rwolf2 Stata module.
Context
Currently, it is only possible to control for multiple testing for hypothesis of the same parameter, against the same null.
E.g. for a set of regression models $s = 1, ..., S$, we can only test that $\beta{ks} = 0$ for a parameter k. In the example above, the parameter to be tested, "X1", needs to be fixed across models. It is not possible to e.g. test more complex hypotheses, as e.g. $\beta{1,1} = 0$, $\beta_{1,2} = 0$, etc.
To Do
bonferroni()andrwolf(). We can draw some inspiration from the rwolf2 Stata module.