estimation.bonferroni

estimation.bonferroni(models, param)

Compute Bonferroni adjusted p-values for multiple hypothesis testing.

For each model, it is assumed that tests to adjust are of the form “param = 0”.

Parameters

Name	Type	Description	Default
models	(list[Feols, Fepois], Feols or Fepois)	A list of models for which the p-values should be adjusted, or a Feols or Fepois object.	required
param	str	The parameter for which the p-values should be adjusted.	required

Returns

Type	Description
pd.DataFrame	A DataFrame containing estimation statistics, including the Bonferroni adjusted p-values.

Examples

from pyfixest.estimation import feols
from pyfixest.utils import get_data
from pyfixest.multcomp import bonferroni

data = get_data().dropna()
fit1 = feols("Y ~ X1", data=data)
fit2 = feols("Y ~ X1 + X2", data=data)
bonf_df = bonferroni([fit1, fit2], param="X1")
bonf_df