code: def setup_class(cls):
      # balanced case
      cls.endog = dta2["StressReduction"]
      cls.groups = dta2["Treatment"]
      cls.alpha = 0.05
      cls.setup_class_()  # in super
  
      # from R
      tukeyhsd2s = np.array(
          [
              1.5,
              1,
              -0.5,
              0.3214915,
              -0.1785085,
              -1.678509,
              2.678509,
              2.178509,
              0.6785085,
              0.01056279,
              0.1079035,
              0.5513904,
          ]
      ).reshape(3, 4, order="F")
      cls.meandiff2 = tukeyhsd2s[:, 0]
      cls.confint2 = tukeyhsd2s[:, 1:3]
      pvals = tukeyhsd2s[:, 3]
      cls.reject2 = pvals < 0.05
  
imports: from statsmodels.compat.python import asbytes
  from io import BytesIO
  import warnings
  import numpy
  import pandas
  import pytest
  from numpy.testing import assert_, assert_allclose, assert_almost_equal, assert_equal, assert_raises
  from statsmodels.stats.libqsturng import qsturng
  from statsmodels.stats.multicomp import tukeyhsd, pairwise_tukeyhsd, MultiComparison
label_desc: Use image node_id 1 for calling the TestTuckeyHSD2 obj's underlying member method code with example usage: obj.setup_class(cls) without return types