diff_diff.SABootstrapResults#

class diff_diff.SABootstrapResults[source]#

Bases: object

Results from Sun-Abraham bootstrap inference.

n_bootstrap#

Number of bootstrap iterations.

Type:: int

weight_type#

Type of bootstrap used (always “pairs” for pairs bootstrap).

Type:: str

alpha#

Significance level used for confidence intervals.

Type:: float

overall_att_se#

Bootstrap standard error for overall ATT.

Type:: float

overall_att_ci#

Bootstrap confidence interval for overall ATT.

Type:: Tuple[float, float]

overall_att_p_value#

Bootstrap p-value for overall ATT.

Type:: float

event_study_ses#

Bootstrap SEs for event study effects.

Type:: Dict[int, float]

event_study_cis#

Bootstrap CIs for event study effects.

Type:: Dict[int, Tuple[float, float]]

event_study_p_values#

Bootstrap p-values for event study effects.

Type:: Dict[int, float]

bootstrap_distribution#

Full bootstrap distribution of overall ATT.

Type:: Optional[np.ndarray]

Methods

__init__(n_bootstrap, weight_type, alpha, ...)

Attributes

`bootstrap_distribution`
`n_bootstrap`
`weight_type`
`alpha`
`overall_att_se`
`overall_att_ci`
`overall_att_p_value`
`event_study_ses`
`event_study_cis`
`event_study_p_values`

__init__(n_bootstrap, weight_type, alpha, overall_att_se, overall_att_ci, overall_att_p_value, event_study_ses, event_study_cis, event_study_p_values, bootstrap_distribution=None)#

Parameters:

n_bootstrap (int)
weight_type (str)
alpha (float)
overall_att_se (float)
overall_att_ci (Tuple[float, float])
overall_att_p_value (float)
event_study_ses (Dict[int, float])
event_study_cis (Dict[int, Tuple[float, float]])
event_study_p_values (Dict[int, float])
bootstrap_distribution (ndarray | None)

Return type:

None

classmethod __new__(*args, **kwargs)#