def get_heterogeneity_stats(self):
"""Get heterogeneity statistics."""
v = self.estimator.get_v(self.dataset)
q_fe = q_gen(self.dataset.y, v, self.dataset.X, 0)
df = self.dataset.y.shape[0] - self.dataset.X.shape[1]
i2 = np.maximum(100.0 * (q_fe - df) / q_fe, 0.0)
h = np.maximum(np.sqrt(q_fe / df), 1.0)
p = ss.chi2.sf(q_fe, df)
return {"Q": q_fe, "p(Q)": p, "I^2": i2, "H": h}
def test_q_gen(vars_with_intercept):
result = q_gen(*vars_with_intercept, 8)
assert round(result[0], 4) == 8.0161
def test_q_gen(vars_with_intercept):
"""Test pymare.stats.q_gen."""
result = q_gen(*vars_with_intercept, 8)
assert round(result[0], 4) == 8.0161