APO_dml_atet: This function calculates the average potential outcomes for...

In MCKnaus/causalDML: Causal Double Machine Learning

This function calculates the average potential outcomes for the average treatment effect on the treated.

Description

This function calculates the average potential outcomes for the average treatment effect on the treated.

Usage

APO_dml_atet(y, m_mat, w_mat, e_mat, cf_mat, treated = 2, norm = 2, cl = NULL)

Arguments

y	A numeric vector containing the outcome variable.
m_mat	n x T+1 matrix with fitted outcome values.
w_mat	Logical matrix of treatment indicators (n x T+1). For example created by prep_w_mat.
e_mat	n x T+1 matrix with (generalized) propensity scores.
cf_mat	Logical matrix with k columns of indicators representing the different folds (for example created by prep_cf_mat).
treated	An integer describing the column number of the treated in w_mat for which ATET should be calculated (default 2).
norm	Controls normalization of IPW weights. norm = 1): overall normalization, norm = 2): normalization in each cross-fitting fold separately (default), otherwise no normalization.
cl	If not NULL, vector with cluster variables.

Value

APO_dmlmt returns a list containing the results and a matrix with the individual values of the doubly robust score.

MCKnaus/causalDML documentation built on June 11, 2025, 12:30 a.m.