diff_diff.CSBootstrapResults

class diff_diff.CSBootstrapResults[source]

Bases: object

Results from Callaway-Sant’Anna multiplier bootstrap inference.

n_bootstrap

Number of bootstrap iterations.

Type:

int

weight_type

Type of bootstrap weights used.

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

group_time_ses

Bootstrap SEs for each ATT(g,t).

Type:

Dict[Tuple[Any, Any], float]

group_time_cis

Bootstrap CIs for each ATT(g,t).

Type:

Dict[Tuple[Any, Any], Tuple[float, float]]

group_time_p_values

Bootstrap p-values for each ATT(g,t).

Type:

Dict[Tuple[Any, Any], float]

event_study_ses

Bootstrap SEs for event study effects.

Type:

Optional[Dict[int, float]]

event_study_cis

Bootstrap CIs for event study effects.

Type:

Optional[Dict[int, Tuple[float, float]]]

event_study_p_values

Bootstrap p-values for event study effects.

Type:

Optional[Dict[int, float]]

group_effect_ses

Bootstrap SEs for group effects.

Type:

Optional[Dict[Any, float]]

group_effect_cis

Bootstrap CIs for group effects.

Type:

Optional[Dict[Any, Tuple[float, float]]]

group_effect_p_values

Bootstrap p-values for group effects.

Type:

Optional[Dict[Any, float]]

bootstrap_distribution

Full bootstrap distribution of overall ATT (if requested).

Type:

Optional[np.ndarray]

__init__(n_bootstrap, weight_type, alpha, overall_att_se, overall_att_ci, overall_att_p_value, group_time_ses, group_time_cis, group_time_p_values, event_study_ses=None, event_study_cis=None, event_study_p_values=None, group_effect_ses=None, group_effect_cis=None, group_effect_p_values=None, bootstrap_distribution=None)
Parameters:
Return type:

None

Methods

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

Attributes

bootstrap_distribution

event_study_cis

event_study_p_values

event_study_ses

group_effect_cis

group_effect_p_values

group_effect_ses

n_bootstrap

weight_type

alpha

overall_att_se

overall_att_ci

overall_att_p_value

group_time_ses

group_time_cis

group_time_p_values

n_bootstrap: int
weight_type: str
alpha: float
overall_att_se: float
overall_att_ci: Tuple[float, float]
overall_att_p_value: float
group_time_ses: Dict[Tuple[Any, Any], float]
group_time_cis: Dict[Tuple[Any, Any], Tuple[float, float]]
group_time_p_values: Dict[Tuple[Any, Any], float]
event_study_ses: Dict[int, float] | None = None
event_study_cis: Dict[int, Tuple[float, float]] | None = None
event_study_p_values: Dict[int, float] | None = None
group_effect_ses: Dict[Any, float] | None = None
group_effect_cis: Dict[Any, Tuple[float, float]] | None = None
group_effect_p_values: Dict[Any, float] | None = None
bootstrap_distribution: ndarray | None = None
__init__(n_bootstrap, weight_type, alpha, overall_att_se, overall_att_ci, overall_att_p_value, group_time_ses, group_time_cis, group_time_p_values, event_study_ses=None, event_study_cis=None, event_study_p_values=None, group_effect_ses=None, group_effect_cis=None, group_effect_p_values=None, bootstrap_distribution=None)
Parameters:
Return type:

None