def test_match_openepi_sampledata(self):
oe_irr = -0.001055
oe_ci = -0.003275, 0.001166
df = ze.load_sample_data(False)
ird = IncidenceRateDifference()
ird.fit(df, exposure='art', outcome='dead', time='t')
npt.assert_allclose(ird.incidence_rate_difference[1], oe_irr, atol=1e-5)
rf = ird.results
npt.assert_allclose(rf.loc[rf.index == '1'][['IRD_LCL', 'IRD_UCL']], [oe_ci], atol=1e-5)
def test_multiple_exposures(self):
df = pd.DataFrame()
df['exp'] = [1]*50 + [0]*50 + [2]*50
df['dis'] = [1]*25 + [0]*25 + [1]*25 + [0]*25 + [1]*25 + [0]*25
df['t'] = 2
ird = IncidenceRateDifference()
ird.fit(df, exposure='exp', outcome='dis', time='t')
assert ird.results.shape[0] == 3
assert list(ird.results.index) == ['Ref:0', '1', '2']
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_incidence_rate_difference_reference_equal_to_0(self, time_data):
ird = IncidenceRateDifference()
ird.fit(time_data, exposure='exp', outcome='dis', time='t')
assert ird.incidence_rate_difference[0] == 0