def test_match_sas_ci(self, data_set):
sas_ci = 0.6757, 1.4799
rr = RiskRatio()
rr.fit(data_set, exposure='exp', outcome='dis')
df = rr.results
npt.assert_allclose(
np.round(df.loc[df.index == '1'][['RR_LCL', 'RR_UCL']], 4),
[sas_ci])
def test_match_sas_sampledata(self):
sas_rd = 0.742118331
sas_se = 0.312612740
sas_ci = 0.402139480, 1.369523870
df = ze.load_sample_data(False)
rr = RiskRatio()
rr.fit(df, exposure='art', outcome='dead')
npt.assert_allclose(rr.risk_ratio[1], sas_rd, rtol=1e-5)
rf = rr.results
npt.assert_allclose(rf.loc[rf.index == '1'][['RR_LCL', 'RR_UCL']], [sas_ci], rtol=1e-5)
npt.assert_allclose(rf.loc[rf.index == '1'][['SD(RR)']], sas_se, rtol=1e-5)
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):
rr = RiskRatio()
rr.fit(multi_exposures, exposure='exp', outcome='dis')
assert rr.results.shape[0] == 3
assert list(rr.results.index) == ['Ref:0', '1', '2']
def test_risk_ratio_equal_to_1(self, data_set):
rr = RiskRatio()
rr.fit(data_set, exposure='exp', outcome='dis')
assert rr.risk_ratio[1] == 1