code: def test_effectsize(self):
      res2 = self.results
      dta = (self.count1, self.nobs1, self.count2, self.nobs2)
      # count1, nobs1, count2, nobs2 = dta
  
      eff, var_eff = effectsize_2proportions(*dta)
      assert_allclose(eff, res2.y_rd, rtol=1e-13)
      assert_allclose(var_eff, res2.v_rd, rtol=1e-13)
  
      eff, var_eff = effectsize_2proportions(*dta, statistic="rr")
      assert_allclose(eff, res2.y_rr, rtol=1e-13)
      assert_allclose(var_eff, res2.v_rr, rtol=1e-13)
  
      eff, var_eff = effectsize_2proportions(*dta, statistic="or")
      assert_allclose(eff, res2.y_or, rtol=1e-13)
      assert_allclose(var_eff, res2.v_or, rtol=1e-13)
  
      eff, var_eff = effectsize_2proportions(*dta, statistic="as")
      assert_allclose(eff, res2.y_as, rtol=1e-13)
      assert_allclose(var_eff, res2.v_as, rtol=1e-13)
  
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 2 for calling the TestEffectsizeBinom obj's underlying member method code with example usage: obj.test_effectsize() without return types