code: def test_evalue_linear_regression(self, mock_fig, estimator_method):
      data = dowhy.datasets.linear_dataset(
          beta=10,
          num_common_causes=5,
          num_samples=1000,
          treatment_is_binary=True,
          stddev_outcome_noise=5,
      )
      model = CausalModel(
          data=data["df"],
          treatment=data["treatment_name"],
          outcome=data["outcome_name"],
          graph=data["gml_graph"],
      )
      identified_estimand = model.identify_effect()
      estimate = model.estimate_effect(
          identified_estimand, method_name=estimator_method
      )
      refute = model.refute_estimate(
          identified_estimand,
          estimate,
          method_name="add_unobserved_common_cause",
          simulation_method="e-value",
      )
  
      assert refute.stats["evalue_upper_ci"] is None
      assert (
          refute.stats["evalue_lower_ci"]
          < refute.stats["evalue_estimate"]
      )
      assert mock_fig.call_count > 0
  
imports: from unittest.mock import patch
  import numpy
  import pytest
  import statsmodels.api
  from pytest import mark
  from sklearn.ensemble import GradientBoostingRegressor
  import dowhy.datasets
  from dowhy import CausalModel
  from dowhy.causal_refuters.evalue_sensitivity_analyzer import EValueSensitivityAnalyzer
  from .base import SimpleRefuter
label_desc: Use image node_id 12 for calling the TestAddUnobservedCommonCauseRefuter obj's underlying member method code with example usage: obj.test_evalue_linear_regression(mock_fig, estimator_method) without return types