moderndid.didinter.container.HeterogeneityResult#

class moderndid.didinter.container.HeterogeneityResult(horizon: int, covariates: list[str], estimates: ndarray, std_errors: ndarray, t_stats: ndarray, ci_lower: ndarray, ci_upper: ndarray, n_obs: int, f_pvalue: float)[source]#

Container for heterogeneous effects analysis.

Attributes:

horizonint: Effect horizon analyzed.
covariateslist[str]: Covariate names.
estimatesnumpy.ndarray: Coefficient estimates for each covariate.
std_errorsnumpy.ndarray: Standard errors for each coefficient.
t_statsnumpy.ndarray: T-statistics for each coefficient.
ci_lowernumpy.ndarray: Lower confidence interval bounds.
ci_uppernumpy.ndarray: Upper confidence interval bounds.
n_obsint: Number of observations in the regression.
f_pvaluefloat: P-value from joint F-test that all covariate coefficients are zero.

Methods

`count`(value, /)	Return number of occurrences of value.
`index`(value[, start, stop])	Return first index of value.

Attributes

`ci_lower`	Lower confidence interval bounds.
`ci_upper`	Upper confidence interval bounds.
`covariates`	Covariate names.
`estimates`	Coefficient estimates for each covariate.
`f_pvalue`	P-value from joint F-test that all covariate coefficients are zero.
`horizon`	Effect horizon analyzed.
`n_obs`	Number of observations in the regression.
`std_errors`	Standard errors for each coefficient.
`t_stats`	T-statistics for each coefficient.