def test_ordinal(self):
family = Binomial()
endog, exog, groups = load_data("gee_ordinal_1.csv",
icept=False)
va = GlobalOddsRatio("ordinal")
mod = OrdinalGEE(endog, exog, groups, None, family, va)
rslt = mod.fit()
# Regression test
cf = np.r_[1.09250002, 0.0217443 , -0.39851092, -0.01812116,
0.03023969, 1.18258516, 0.01803453, -1.10203381]
assert_almost_equal(rslt.params, cf, decimal=5)
# Regression test
se = np.r_[0.10883461, 0.10330197, 0.11177088, 0.05486569,
0.05997153, 0.09168148, 0.05953324, 0.0853862]
assert_almost_equal(rslt.bse, se, decimal=5)
# Check that we get the correct results type
assert_equal(type(rslt), OrdinalGEEResultsWrapper)
assert_equal(type(rslt._results), OrdinalGEEResults)
def test_ordinal(self):
family = Binomial()
endog, exog, groups = load_data("gee_ordinal_1.csv",
icept=False)
va = GlobalOddsRatio("ordinal")
mod = OrdinalGEE(endog, exog, groups, None, family, va)
rslt = mod.fit()
# Regression test
cf = np.r_[1.09250002, 0.0217443 , -0.39851092, -0.01812116,
0.03023969, 1.18258516, 0.01803453, -1.10203381]
assert_almost_equal(rslt.params, cf, decimal=5)
# Regression test
se = np.r_[0.10883461, 0.10330197, 0.11177088, 0.05486569,
0.05997153, 0.09168148, 0.05953324, 0.0853862]
assert_almost_equal(rslt.bse, se, decimal=5)
# Check that we get the correct results type
assert_equal(type(rslt), OrdinalGEEResultsWrapper)
assert_equal(type(rslt._results), OrdinalGEEResults)
def test_wrapper(self):
endog, exog, groups = load_data("gee_ordinal_1.csv", icept=False)
endog = pd.Series(endog, name='yendog')
exog = pd.DataFrame(exog)
groups = pd.Series(groups, name='the_group')
family = Binomial()
va = GlobalOddsRatio("ordinal")
mod = OrdinalGEE(endog, exog, groups, None, family, va)
rslt2 = mod.fit()
check_wrapper(rslt2)
def test_wrapper(self):
endog, exog, groups = load_data("gee_ordinal_1.csv",
icept=False)
endog = pd.Series(endog, name='yendog')
exog = pd.DataFrame(exog)
groups = pd.Series(groups, name='the_group')
family = Binomial()
va = GlobalOddsRatio("ordinal")
mod = OrdinalGEE(endog, exog, groups, None, family, va)
rslt2 = mod.fit()
check_wrapper(rslt2)
def test_ordinal(self):
family = Binomial()
endog, exog, groups = load_data("gee_ordinal_1.csv", icept=False)
v = GlobalOddsRatio("ordinal")
md = OrdinalGEE(endog, exog, groups, None, family, v)
mdf = md.fit()
cf = np.r_[1.09250002, 0.0217443, -0.39851092, -0.01812116, 0.03023969,
1.18258516, 0.01803453, -1.10203381]
se = np.r_[0.10883461, 0.10330197, 0.11177088, 0.05486569, 0.05997153,
0.09168148, 0.05953324, 0.0853862]
assert_almost_equal(mdf.params, cf, decimal=5)
assert_almost_equal(mdf.bse, se, decimal=5)
def test_ordinal(self):
family = Binomial()
endog, exog, groups = load_data("gee_ordinal_1.csv",
icept=False)
v = GlobalOddsRatio("ordinal")
md = OrdinalGEE(endog, exog, groups, None, family, v)
mdf = md.fit()
cf = np.r_[1.09250002, 0.0217443 , -0.39851092, -0.01812116,
0.03023969, 1.18258516, 0.01803453, -1.10203381]
se = np.r_[0.10883461, 0.10330197, 0.11177088, 0.05486569,
0.05997153, 0.09168148, 0.05953324, 0.0853862]
assert_almost_equal(mdf.params, cf, decimal=5)
assert_almost_equal(mdf.bse, se, decimal=5)
def setup_class(cls):
family = Binomial()
endog, exog, groups = load_data("gee_ordinal_1.csv", icept=False)
va = GlobalOddsRatio("ordinal")
cls.mod = OrdinalGEE(endog, exog, groups, None, family, va)
cls.start_params = np.array([
1.09250002, 0.0217443, -0.39851092, -0.01812116, 0.03023969,
1.18258516, 0.01803453, -1.10203381
])
