def test_ftest_power():
#equivalence ftest, ttest
for alpha in [0.01, 0.05, 0.1, 0.20, 0.50]:
res0 = smp.ttest_power(0.01, 200, alpha)
res1 = smp.ftest_power(0.01, 199, 1, alpha=alpha, ncc=0)
assert_almost_equal(res1, res0, decimal=6)
#example from Gplus documentation F-test ANOVA
#Total sample size:200
#Effect size "f":0.25
#Beta/alpha ratio:1
#Result:
#Alpha:0.1592
#Power (1-beta):0.8408
#Critical F:1.4762
#Lambda: 12.50000
res1 = smp.ftest_anova_power(0.25, 200, 0.1592, k_groups=10)
res0 = 0.8408
assert_almost_equal(res1, res0, decimal=4)
# TODO: no class yet
# examples agains R::pwr
res2 = Holder()
#> rf = pwr.f2.test(u=5, v=199, f2=0.1**2, sig.level=0.01)
#> cat_items(rf, "res2.")
res2.u = 5
res2.v = 199
res2.f2 = 0.01
res2.sig_level = 0.01
res2.power = 0.0494137732920332
res2.method = 'Multiple regression power calculation'
res1 = smp.ftest_power(np.sqrt(res2.f2), res2.v, res2.u,
alpha=res2.sig_level, ncc=1)
assert_almost_equal(res1, res2.power, decimal=5)
res2 = Holder()
#> rf = pwr.f2.test(u=5, v=199, f2=0.3**2, sig.level=0.01)
#> cat_items(rf, "res2.")
res2.u = 5
res2.v = 199
res2.f2 = 0.09
res2.sig_level = 0.01
res2.power = 0.7967191006290872
res2.method = 'Multiple regression power calculation'
res1 = smp.ftest_power(np.sqrt(res2.f2), res2.v, res2.u,
alpha=res2.sig_level, ncc=1)
assert_almost_equal(res1, res2.power, decimal=5)
res2 = Holder()
#> rf = pwr.f2.test(u=5, v=19, f2=0.3**2, sig.level=0.1)
#> cat_items(rf, "res2.")
res2.u = 5
res2.v = 19
res2.f2 = 0.09
res2.sig_level = 0.1
res2.power = 0.235454222377575
res2.method = 'Multiple regression power calculation'
res1 = smp.ftest_power(np.sqrt(res2.f2), res2.v, res2.u,
alpha=res2.sig_level, ncc=1)
assert_almost_equal(res1, res2.power, decimal=5)
def test_ftest_power():
#equivalence ftest, ttest
for alpha in [0.01, 0.05, 0.1, 0.20, 0.50]:
res0 = smp.ttest_power(0.01, 200, alpha)
res1 = smp.ftest_power(0.01, 199, 1, alpha=alpha, ncc=0)
assert_almost_equal(res1, res0, decimal=6)
#example from Gplus documentation F-test ANOVA
#Total sample size:200
#Effect size "f":0.25
#Beta/alpha ratio:1
#Result:
#Alpha:0.1592
#Power (1-beta):0.8408
#Critical F:1.4762
#Lambda: 12.50000
res1 = smp.ftest_anova_power(0.25, 200, 0.1592, k_groups=10)
res0 = 0.8408
assert_almost_equal(res1, res0, decimal=4)
# TODO: no class yet
# examples agains R::pwr
res2 = Holder()
#> rf = pwr.f2.test(u=5, v=199, f2=0.1**2, sig.level=0.01)
#> cat_items(rf, "res2.")
res2.u = 5
res2.v = 199
res2.f2 = 0.01
res2.sig_level = 0.01
res2.power = 0.0494137732920332
res2.method = 'Multiple regression power calculation'
res1 = smp.ftest_power(np.sqrt(res2.f2), res2.v, res2.u,
alpha=res2.sig_level, ncc=1)
assert_almost_equal(res1, res2.power, decimal=5)
res2 = Holder()
#> rf = pwr.f2.test(u=5, v=199, f2=0.3**2, sig.level=0.01)
#> cat_items(rf, "res2.")
res2.u = 5
res2.v = 199
res2.f2 = 0.09
res2.sig_level = 0.01
res2.power = 0.7967191006290872
res2.method = 'Multiple regression power calculation'
res1 = smp.ftest_power(np.sqrt(res2.f2), res2.v, res2.u,
alpha=res2.sig_level, ncc=1)
assert_almost_equal(res1, res2.power, decimal=5)
res2 = Holder()
#> rf = pwr.f2.test(u=5, v=19, f2=0.3**2, sig.level=0.1)
#> cat_items(rf, "res2.")
res2.u = 5
res2.v = 19
res2.f2 = 0.09
res2.sig_level = 0.1
res2.power = 0.235454222377575
res2.method = 'Multiple regression power calculation'
res1 = smp.ftest_power(np.sqrt(res2.f2), res2.v, res2.u,
alpha=res2.sig_level, ncc=1)
assert_almost_equal(res1, res2.power, decimal=5)
def calculate_power(difference, n_observation, alpha=0.05, alternatives='smaller'):
return smp.ttest_power(difference, nobs=n_observation, alpha=alpha, alternative=alternatives)
