code: def setup_class(cls):
      # example from book Applied Meta-Analysis with R
      data = [
          ["Carroll", 94, 22, 60, 92, 20, 60],
          ["Grant", 98, 21, 65, 92, 22, 65],
          ["Peck", 98, 28, 40, 88, 26, 40],
          ["Donat", 94, 19, 200, 82, 17, 200],
          ["Stewart", 98, 21, 50, 88, 22, 45],
          ["Young", 96, 21, 85, 92, 22, 85],
      ]
      colnames = [
          "study",
          "mean_t",
          "sd_t",
          "n_t",
          "mean_c",
          "sd_c",
          "n_c",
      ]
      dframe = pd.DataFrame(data, columns=colnames)
      cls.dta = np.asarray(
          dframe[["mean_t", "sd_t", "n_t", "mean_c", "sd_c", "n_c"]]
      ).T
      cls.row_names = dframe["study"]
  
imports: import io
  import numpy
  import pandas
  import pytest
  from numpy.testing import assert_equal, assert_allclose
  from statsmodels.regression.linear_model import WLS
  from statsmodels.genmod.generalized_linear_model import GLM
  from statsmodels.stats.meta_analysis import effectsize_smd, effectsize_2proportions, combine_effects, _fit_tau_iterative, _fit_tau_mm, _fit_tau_iter_mm
  from .results import results_meta
label_desc: Use image node_id 1 for calling the TestEffSmdMeta obj's underlying member method code with example usage: obj.setup_class(cls) without return types