moderndid.didinter.container.DIDInterResult#
- class moderndid.didinter.container.DIDInterResult(effects: EffectsResult, placebos: PlacebosResult | None = None, ate: ATEResult | None = None, n_units: int = 0, n_switchers: int = 0, n_never_switchers: int = 0, ci_level: float = 95.0, effects_equal_test: dict | None = None, placebo_joint_test: dict | None = None, influence_effects: ndarray | None = None, influence_placebos: ndarray | None = None, heterogeneity: list | None = None, estimation_params: dict = {}, vcov_warnings: list = [])[source]#
Bases:
NamedTupleContainer for DIDInter estimation results.
This class implements the
maketablesplug-in interface for publication-quality tables. See Publication Tables with maketables.- Attributes:
- effects
EffectsResult Treatment effects for each post-treatment horizon.
- placebos
PlacebosResult, optional Placebo effects for each pre-treatment horizon.
- ate
ATEResult, optional Average total effect across all horizons.
- n_units
int Total number of units in the sample.
- n_switchers
int Number of switchers in the sample.
- n_never_switchers
int Number of never-switchers in the sample.
- ci_level
float Confidence level used for intervals (e.g., 95.0).
- effects_equal_test
dict, optional Test for equality of effects across horizons.
- placebo_joint_test
dict, optional Joint test that all placebo effects are zero.
- influence_effects
numpy.ndarray, optional Influence function for effects.
- influence_placebos
numpy.ndarray, optional Influence function for placebos.
- heterogeneity
list[HeterogeneityResult], optional Heterogeneous effects analysis results for each horizon.
- estimation_params
dict Parameters used for estimation.
- vcov_warnings
list Variance-covariance warnings.
- effects
Methods
count(value, /)Return number of occurrences of value.
index(value[, start, stop])Return first index of value.
Attributes
Average total effect across all horizons.
Confidence level used for intervals.
Treatment effects for each post-treatment horizon.
Test for equality of effects across horizons.
Parameters used for estimation.
Heterogeneous effects analysis results.
Influence function for effects.
Influence function for placebos.
Number of never-switchers in the sample.
Number of switchers in the sample.
Total number of units in the sample.
Joint test that all placebo effects are zero.
Placebo effects for each pre-treatment horizon.
Variance-covariance warnings.