code: def test_two_level_glm_novar():
      X = np.random.normal(0, 1, size=(100, 10))
      y = np.random.normal(0, 1, size=(100, 50))
      vy = np.zeros((100, 50))
      beta, s2, dof = two_level_glm(y, vy, X)
      beta_error = np.mean(beta**2)
      s2_error = np.abs(np.mean(s2) - 1)
      print(f"Errors: {beta_error:f} (beta), {s2_error:f} (s2)")
      assert beta_error < 0.1
      assert s2_error < 0.1
  
file_path: nipy/nipy/algorithms/statistics/tests/test_mixed_effects.py
imports: import numpy
  import numpy.random
  import pytest
  from numpy.testing import assert_almost_equal, assert_array_almost_equal
  from ..bayesian_mixed_effects import two_level_glm
  from ..mixed_effects_stat import generate_data, mfx_stat, one_sample_ftest, one_sample_ttest, t_stat, two_sample_ftest, two_sample_ttest
label_desc: Use image node_id 8 for calling a global function with example usage: test_two_level_glm_novar() without return types