code: def sensitivity_e_value(
      data: pd.DataFrame,
      target_estimand: IdentifiedEstimand,
      estimate: CausalEstimate,
      treatment_name: List[str],
      outcome_name: List[str],
      plot_estimate: bool = True,
  ) -> EValueSensitivityAnalyzer:
      if not isinstance(estimate.estimator, RegressionEstimator):
          raise NotImplementedError(
              "E-Value sensitivity analysis is currently only implemented RegressionEstimator."
          )
  
      if (
          estimate.estimator._effect_modifier_names is not None
          and len(estimate.estimator._effect_modifier_names) > 0
      ):
          raise NotImplementedError(
              "The current implementation does not support effect modifiers"
          )
  
      analyzer = EValueSensitivityAnalyzer(
          estimate=estimate,
          estimand=target_estimand,
          data=data,
          treatment_name=treatment_name[0],
          outcome_name=outcome_name[0],
      )
      analyzer.check_sensitivity(data, plot=plot_estimate)
      return analyzer
  
imports: import copy
  import logging
  import math
  from typing import Dict, List, Optional, Union
  import numpy
  import pandas
  import scipy.stats
  import statsmodels.api
  from sklearn.linear_model import LogisticRegression
  from sklearn.preprocessing import StandardScaler
  from tqdm.auto import tqdm
  from dowhy.causal_estimator import CausalEstimate
  from dowhy.causal_estimators.econml import Econml
  from dowhy.causal_estimators.linear_regression_estimator import LinearRegressionEstimator
  from dowhy.causal_estimators.regression_estimator import RegressionEstimator
  from dowhy.causal_identifier.identified_estimand import IdentifiedEstimand
  from dowhy.causal_refuter import CausalRefutation, CausalRefuter, choose_variables
  from dowhy.causal_refuters.evalue_sensitivity_analyzer import EValueSensitivityAnalyzer
  from dowhy.causal_refuters.linear_sensitivity_analyzer import LinearSensitivityAnalyzer
label_desc: Use image node_id 9 for calling a global function with example usage: sensitivity_e_value(data, target_estimand, estimate, treatment_name, outcome_name, plot_estimate) and returns: analyzer