class_docstr: Compute effect of treatment using the regression discontinuity method.
  
  Estimates effect by transforming the problem to an instrumental variables
  problem.
  
  Supports additional parameters as listed below.
code: def estimate_effect(
      self,
      data: pd.DataFrame,
      treatment_value: Any = 1,
      control_value: Any = 0,
      target_units=None,
      **_,
  ):
      self._target_units = target_units
      self._treatment_value = treatment_value
      self._control_value = control_value
  
      est = self.iv_estimator.estimate_effect(
          self._local_df,
          treatment_value=treatment_value,
          control_value=control_value,
          target_units=target_units,
      )
  
      est.add_estimator(self)
      return est
  
file_path: dowhy/dowhy/causal_estimators/regression_discontinuity_estimator.py
imports: from typing import Any, List, Optional, Union
  import numpy
  import pandas
  from dowhy.causal_estimator import CausalEstimator
  from dowhy.causal_estimators.instrumental_variable_estimator import InstrumentalVariableEstimator
  from dowhy.causal_identifier import IdentifiedEstimand
label_desc: Use image node_id 3 for calling the RegressionDiscontinuityEstimator obj's underlying member method code with example usage: obj.estimate_effect(data, treatment_value, control_value, target_units) and returns: est