code: def test_results_other(self):
      res1 = self.res1  # numpy
      resp = self.resp  # pandas
  
      param_names_np = ["x1", "x2", "x3", "0/1", "1/2"]
      param_names_pd = [
          "pared",
          "public",
          "gpa",
          "unlikely/somewhat likely",
          "somewhat likely/very likely",
      ]
  
      assert res1.model.data.param_names == param_names_np
      assert self.resp.model.data.param_names == param_names_pd
      assert self.resp.model.endog_names == "apply"
  
      # results
      if hasattr(self, "pred_table"):
          table = res1.pred_table()
          assert_equal(table.values, self.pred_table)
  
      # smoke test
      res1.summary()
  
      # inherited
      tt = res1.t_test(np.eye(len(res1.params)))
      assert_allclose(tt.pvalue, res1.pvalues, rtol=1e-13)
  
      tt = resp.t_test(["pared", "public", "gpa"])  # pandas names
      assert_allclose(tt.pvalue, res1.pvalues[:3], rtol=1e-13)
  
      pred = res1.predict(exog=res1.model.exog[-5:])
      fitted = res1.predict()
      assert_allclose(pred, fitted[-5:], rtol=1e-13)
  
      pred = resp.predict(exog=resp.model.data.orig_exog.iloc[-5:])
      fitted = resp.predict()
      assert_allclose(pred, fitted[-5:], rtol=1e-13)
  
      dataf = self.resf.model.data.frame  # is a dict
      dataf_df = pd.DataFrame.from_dict(dataf)
      pred = self.resf.predict(exog=dataf_df.iloc[-5:])
      fitted = self.resf.predict()
      assert_allclose(pred, fitted[-5:], rtol=1e-13)
  
      n, k = res1.model.exog.shape
      assert_equal(self.resf.df_resid, n - (k + 2))
  
      # check wrapper
      assert resp.params.index.tolist() == resp.model.exog_names
      assert resp.bse.index.tolist() == resp.model.exog_names
  
imports: import warnings
  import numpy
  from numpy.testing import assert_allclose, assert_equal
  import pandas
  import pytest
  import scipy.stats
  from statsmodels.discrete.discrete_model import Logit
  from statsmodels.miscmodels.ordinal_model import OrderedModel
  from statsmodels.tools.sm_exceptions import HessianInversionWarning
  from statsmodels.tools.tools import add_constant
  from .results.results_ordinal_model import data_store
label_desc: Use image node_id 5 for calling the CheckOrdinalModelMixin obj's underlying member method code with example usage: obj.test_results_other() without return types