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)
