RegressionDiscontinuity

class causalpy.experiments.regression_discontinuity.RegressionDiscontinuity

A class to analyse sharp regression discontinuity experiments.

Parameters:

• data (DataFrame) – A pandas dataframe

• formula (str) – A statistical model formula

• treatment_threshold (float) – A scalar threshold value at which the treatment is applied

• model – A PyMC model

• running_variable_name (str) – The name of the predictor variable that the treatment threshold is based upon

• epsilon (float) – A small scalar value which determines how far above and below the treatment threshold to evaluate the causal impact.

• bandwidth (float) – Data outside of the bandwidth (relative to the discontinuity) is not used to fit the model.

Example

>>> import causalpy as cp
>>> df = cp.load_data("rd")
>>> seed = 42
>>> result = cp.RegressionDiscontinuity(
...     df,
...     formula="y ~ 1 + x + treated + x:treated",
...     model=cp.pymc_models.LinearRegression(
...         sample_kwargs={
...             "draws": 100,
...             "target_accept": 0.95,
...             "random_seed": seed,
...             "progressbar": False,
...         },
...     ),
...     treatment_threshold=0.5,
... )

Methods

RegressionDiscontinuity.__init__(data, ...)
RegressionDiscontinuity.get_plot_data(*args, ...)	Recover the data of an experiment along with the prediction and causal impact information.
RegressionDiscontinuity.get_plot_data_bayesian(...)	Abstract method for recovering plot data.
RegressionDiscontinuity.get_plot_data_ols(...)	Abstract method for recovering plot data.
RegressionDiscontinuity.input_validation()	Validate the input data and model formula for correctness
RegressionDiscontinuity.plot(*args, **kwargs)	Plot the model.
RegressionDiscontinuity.print_coefficients([...])	Ask the model to print its coefficients.
RegressionDiscontinuity.summary([round_to])	Print summary of main results and model coefficients

Attributes

idata	Return the InferenceData object of the model.
supports_bayes
supports_ols

__init__(data, formula, treatment_threshold, model=None, running_variable_name='x', epsilon=0.001, bandwidth=inf, **kwargs)

Parameters:

• data (DataFrame)

• formula (str)

• treatment_threshold (float)

• running_variable_name (str)

• epsilon (float)

• bandwidth (float)

classmethod __new__(*args, **kwargs)