def test_match_r_stddiff(self):
# Simulated data for variable detection and standardized differences
df = pd.DataFrame()
df['treat'] = [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]
df['bin'] = [0, 1, 0, np.nan, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1]
df['con'] = [
0.1, 0.0, 1.0, 1.1, 2.2, 1.3, 0.1, 0.5, 0.9, 0.5, 0.3, 0.2, 0.7,
0.9, 1.4
]
df['dis'] = [0, 1, 3, 2, 1, 0, 0, 0, 0, 0, 1, 3, 2, 2, 1]
df['cat'] = [1, 2, 3, 1, 1, 2, 3, 1, 3, 2, 1, 2, 3, 2, 1]
ipt = IPTW(df, treatment='treat', stabilized=True)
ipt.regression_models('bin + con + dis + C(cat)')
ipt.fit()
smd = ipt.standardized_mean_differences()
npt.assert_allclose(np.array(smd['smd_u']),
np.array([0.342997, 0.0, 0.06668, -0.513553]),
rtol=1e-4) # for unweighted
# TODO need to find an R package or something that calculates weighted SMD
# currently compares to my own calculations
npt.assert_allclose(np.array(smd['smd_w']),
np.array([0.206072, -0.148404, 0.035752,
0.085844]),
rtol=1e-4) # for weighted
def test_match_r_stddiff(self):
# Simulated data for variable detection and standardized differences
df = pd.DataFrame()
df['y'] = [1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0]
df['treat'] = [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]
df['bin'] = [0, 1, 0, np.nan, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1]
df['con'] = [
0.1, 0.0, 1.0, 1.1, 2.2, 1.3, 0.1, 0.5, 0.9, 0.5, 0.3, 0.2, 0.7,
0.9, 1.4
]
df['dis'] = [0, 1, 3, 2, 1, 0, 0, 0, 0, 0, 1, 3, 2, 2, 1]
df['cat'] = [1, 2, 3, 1, 1, 2, 3, 1, 3, 2, 1, 2, 3, 2, 1]
ipt = IPTW(df, treatment='treat', outcome='y')
ipt.treatment_model(model_denominator='bin + con + dis + C(cat)',
print_results=False)
ipt.marginal_structural_model('treat')
ipt.fit()
smd = ipt.standardized_mean_differences()
npt.assert_allclose(np.array(smd['smd_u']),
np.array([0.342997, 0.0, 0.06668, -0.513553]),
rtol=1e-4) # for unweighted
# TODO need to find an R package or something that calculates weighted SMD
# currently compares to my own calculations
npt.assert_allclose(np.array(smd['smd_w']),
np.array([0.206072, -0.148404, 0.035683,
0.085775]),
rtol=1e-4) # for weighted
def test_standardized_differences(self, sdata):
ipt = IPTW(sdata, treatment='art', stabilized=True)
ipt.regression_models('male + age0 + cd40 + dvl0')
ipt.fit()
smd = ipt.standardized_mean_differences()
npt.assert_allclose(np.array(smd['smd_u']),
np.array([-0.015684, 0.022311, -0.4867, -0.015729]),
rtol=1e-4) # for unweighted
# TODO find R package to test these weighted SMD's
npt.assert_allclose(np.array(smd['smd_w']),
np.array([-0.097789, -0.012395, -0.018591, 0.050719]),
rtol=1e-4) # for weighted
def test_standardized_differences(self, sdata):
ipt = IPTW(sdata, treatment='art', outcome='dead')
ipt.treatment_model(model_denominator='male + age0 + cd40 + dvl0', print_results=False)
ipt.marginal_structural_model('art')
ipt.fit()
smd = ipt.standardized_mean_differences()
npt.assert_allclose(np.array(smd['smd_u']),
np.array([-0.015684, 0.022311, -0.4867, -0.015729]),
rtol=1e-4) # for unweighted
# TODO find R package to test these weighted SMD's
npt.assert_allclose(np.array(smd['smd_w']),
np.array([-0.097789, -0.012395, -0.018591, 0.050719]),
rtol=1e-4) # for weighted