def test_single_model_does_not_break(self): df = load_monotone_missing_data() ipm = IPMW(df, missing_variable=['B', 'C'], stabilized=False, monotone=True) ipm.regression_models(model_denominator='L') ipm.fit() x = ipm.Weight
def test_monotone_example(self): # TODO find R or SAS to test against df = load_monotone_missing_data() ipm = IPMW(df, missing_variable=['B', 'C'], stabilized=False, monotone=True) ipm.regression_models(model_denominator=['L + A', 'L + B']) ipm.fit() df['w'] = ipm.Weight dfs = df.dropna(subset=['w']) npt.assert_allclose(np.average(dfs['B'], weights=dfs['w']), 0.41877344861340654) npt.assert_allclose(np.average(dfs['C'], weights=dfs['w']), 0.5637116735464095)