def test_match_sas_ci(self, data_set):
sas_ci = 0.4566, 2.1902
ord = OddsRatio()
ord.fit(data_set, exposure='exp', outcome='dis')
df = ord.results
npt.assert_allclose(df.loc[df.index == '1'][['OR_LCL', 'OR_UCL']],
[sas_ci],
rtol=1e-4)
def test_match_sas_sampledata(self):
sas_or = 0.7036
sas_se = 0.361479191
sas_ci = 0.3465, 1.4290
df = ze.load_sample_data(False)
ord = OddsRatio()
ord.fit(df, exposure='art', outcome='dead')
npt.assert_allclose(ord.odds_ratio[1], sas_or, rtol=1e-4)
rf = ord.results
npt.assert_allclose(rf.loc[rf.index == '1'][['OR_LCL', 'OR_UCL']], [sas_ci], rtol=1e-3)
npt.assert_allclose(rf.loc[rf.index == '1'][['SD(OR)']], sas_se, rtol=1e-4)
def measures_check():
# 7) Check measures plots
data_set = load_sample_data(False)
rr = RiskRatio()
rr.fit(data_set, exposure='art', outcome='dead')
rr.plot(fmt='*', ecolor='r', barsabove=True, markersize=25)
plt.show()
rd = RiskDifference()
rd.fit(data_set, exposure='art', outcome='dead')
rd.plot()
plt.show()
ord = OddsRatio()
ord.fit(data_set, exposure='art', outcome='dead')
ord.plot()
plt.show()
irr = IncidenceRateRatio()
irr.fit(data_set, exposure='art', outcome='dead', time='t')
irr.plot()
plt.show()
ird = IncidenceRateDifference()
ird.fit(data_set, exposure='art', outcome='dead', time='t')
ird.plot()
plt.show()
def test_multiple_exposures(self, multi_exposures):
ord = OddsRatio()
ord.fit(multi_exposures, exposure='exp', outcome='dis')
assert ord.results.shape[0] == 3
assert list(ord.results.index) == ['Ref:0', '1', '2']
def test_odds_ratio_equal_to_1(self, data_set):
ord = OddsRatio()
ord.fit(data_set, exposure='exp', outcome='dis')
assert ord.odds_ratio[1] == 1