code: def setup_method(self):
      self.n_success = np.array([73, 90, 114, 75])
      self.nobs = np.array([86, 93, 136, 82])
  
      self.res_ppt_pvals_raw = np.array(
          [
              0.00533824886503131,
              0.8327574849753566,
              0.1880573726722516,
              0.002026764254350234,
              0.1309487516334318,
              0.1076118730631731,
          ]
      )
      self.res_ppt_pvals_holm = np.array(
          [
              0.02669124432515654,
              0.8327574849753566,
              0.4304474922526926,
              0.0121605855261014,
              0.4304474922526926,
              0.4304474922526926,
          ]
      )
  
      res_prop_test = Holder()
      res_prop_test.statistic = 11.11938768628861
      res_prop_test.parameter = 3
      res_prop_test.p_value = 0.011097511366581344
      res_prop_test.estimate = np.array(
          [
              0.848837209302326,
              0.967741935483871,
              0.838235294117647,
              0.9146341463414634,
          ]
      ).reshape(4, 1, order="F")
      res_prop_test.null_value = """NULL"""
      res_prop_test.conf_int = """NULL"""
      res_prop_test.alternative = "two.sided"
      res_prop_test.method = (
          "4-sample test for equality of proportions "
          + "without continuity correction"
      )
      res_prop_test.data_name = "smokers2 out of patients"
      self.res_prop_test = res_prop_test
  
      # > pt = prop.test(smokers2, patients, p=rep(c(0.9), 4), correct=FALSE)
      # > cat_items(pt, "res_prop_test_val.")
      res_prop_test_val = Holder()
      res_prop_test_val.statistic = np.array(
          [13.20305530710751]
      ).reshape(1, 1, order="F")
      res_prop_test_val.parameter = np.array([4]).reshape(
          1, 1, order="F"
      )
      res_prop_test_val.p_value = 0.010325090041836
      res_prop_test_val.estimate = np.array(
          [
              0.848837209302326,
              0.967741935483871,
              0.838235294117647,
              0.9146341463414634,
          ]
      ).reshape(4, 1, order="F")
      res_prop_test_val.null_value = np.array(
          [0.9, 0.9, 0.9, 0.9]
      ).reshape(4, 1, order="F")
      res_prop_test_val.conf_int = """NULL"""
      res_prop_test_val.alternative = "two.sided"
      res_prop_test_val.method = "4-sample test for given proportions without continuity correction"
      res_prop_test_val.data_name = (
          "smokers2 out of patients, null probabilities rep(c(0.9), 4)"
      )
      self.res_prop_test_val = res_prop_test_val
  
      # > pt = prop.test(smokers2[1], patients[1], p=0.9, correct=FALSE)
      # > cat_items(pt, "res_prop_test_1.")
      res_prop_test_1 = Holder()
      res_prop_test_1.statistic = 2.501291989664086
      res_prop_test_1.parameter = 1
      res_prop_test_1.p_value = 0.113752943640092
      res_prop_test_1.estimate = 0.848837209302326
      res_prop_test_1.null_value = 0.9
      res_prop_test_1.conf_int = np.array(
          [0.758364348004061, 0.9094787701686766]
      )
      res_prop_test_1.alternative = "two.sided"
      res_prop_test_1.method = (
          "1-sample proportions test without continuity correction"
      )
      res_prop_test_1.data_name = (
          "smokers2[1] out of patients[1], null probability 0.9"
      )
      self.res_prop_test_1 = res_prop_test_1
  
imports: import warnings
  import numpy
  from numpy.testing import assert_allclose, assert_almost_equal, assert_array_less, assert_equal, assert_raises
  import pandas
  import pytest
  import statsmodels.stats.proportion
  from statsmodels.stats.proportion import confint_proportions_2indep, multinomial_proportions_confint, power_proportions_2indep, proportion_confint, samplesize_proportions_2indep_onetail, score_test_proportions_2indep
  from statsmodels.tools.sm_exceptions import HypothesisTestWarning
  from statsmodels.tools.testing import Holder
  from statsmodels.stats.tests.results.results_proportion import res_binom, res_binom_methods
label_desc: Use image node_id 1 for calling the TestProportion obj's underlying member method code with example usage: obj.setup_method() without return types