APO_dml: This function estimates the average potential outcomes for...

In MCKnaus/causalDML: Causal Double Machine Learning

This function estimates the average potential outcomes for all treatment levels.

Description

This function estimates the average potential outcomes for all treatment levels.

Usage

APO_dml(y, m_mat, w_mat, e_mat, cf_mat, 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 propensity scores.
cf_mat	Logical matrix with k columns of indicators representing the different folds (for example created by prep_cf_mat).
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

Returns an APO_dml object:

results	Point estimate and standard error of APOs.
gamma	n x T+1 matrix containing the APO DR scores.
y	Vector of outcomes used in estimation.
m_mat	Matrix of outcome predictions used in estimation.
w_mat	Matrix of treatment indicators (n x T+1) used in estimation.
e_mat	Matrix of propensity score used in estimation.
cf_mat	Matrix with k columns of indicators representing the different folds used in estimation.
cl	Cluster variable if specified.

MCKnaus/causalDML documentation built on Aug. 19, 2023, 5:47 p.m.