moderndid.DDDMultiPeriodRCResult#

class moderndid.DDDMultiPeriodRCResult(att: ndarray, se: ndarray, uci: ndarray, lci: ndarray, groups: ndarray, times: ndarray, glist: ndarray, tlist: ndarray, inf_func_mat: ndarray, n: int, args: dict, unit_groups: ndarray)[source]#

Container for multi-period DDD repeated cross-section estimation results.

This class implements the maketables plug-in interface for publication-quality tables. See Publication Tables with maketables.

Attributes:

attnumpy.ndarray: Array of ATT(g,t) point estimates.
senumpy.ndarray: Array of standard errors for each ATT(g,t).
ucinumpy.ndarray: Array of upper confidence interval bounds.
lcinumpy.ndarray: Array of lower confidence interval bounds.
groupsnumpy.ndarray: Array of treatment cohort identifiers for each estimate.
timesnumpy.ndarray: Array of time period identifiers for each estimate.
glistnumpy.ndarray: Unique treatment cohorts.
tlistnumpy.ndarray: Unique time periods.
inf_func_matnumpy.ndarray: Matrix of influence functions (n_obs x n_estimates).
nint: Number of observations (not units, since this is RCS).
argsdict: Arguments used for estimation.
unit_groupsnumpy.ndarray: Array of treatment group for each observation (length n).

Methods

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

Attributes

`args`	Arguments used for estimation.
`att`	Array of ATT(g,t) point estimates.
`glist`	Unique treatment cohorts.
`groups`	Array of treatment cohort identifiers for each estimate.
`inf_func_mat`	Matrix of influence functions (n_obs x n_estimates).
`lci`	Array of lower confidence interval bounds.
`n`	Number of observations.
`se`	Array of standard errors for each ATT(g,t).
`times`	Array of time period identifiers for each estimate.
`tlist`	Unique time periods.
`uci`	Array of upper confidence interval bounds.
`unit_groups`	Array of treatment group for each observation.