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
| models |
A supported model object (Feols, Fepois, Feiv, FixestMulti) or a list of |
Feols, Fepois & Feiv models. |
required |
| param |
str |
The parameter for which the p-values should be adjusted. |
required |
Returns
|
pd.DataFrame |
A DataFrame containing estimation statistics, including the Bonferroni adjusted p-values. |
Examples
import pyfixest as pf
from pyfixest.utils import get_data
data = get_data().dropna()
fit1 = pf.feols("Y ~ X1", data=data)
fit2 = pf.feols("Y ~ X1 + X2", data=data)
bonf_df = pf.bonferroni([fit1, fit2], param="X1")
bonf_df
| Estimate |
-1.001930 |
-0.995197 |
| Std. Error |
0.084823 |
0.082194 |
| t value |
-11.811964 |
-12.107957 |
| Pr(>|t|) |
0.000000 |
0.000000 |
| 2.5% |
-1.168383 |
-1.156490 |
| 97.5% |
-0.835476 |
-0.833904 |
| Bonferroni Pr(>|t|) |
0.000000 |
0.000000 |