Description Usage Arguments Value
This function estimates treatment effects for binary and multiple treatments using Double Machine Learning.
1 2 3 |
x |
Matrix of covariates (N x p matrix) |
t |
Vector of treament indicators. Will be ordered from 0 to T-1. |
y |
Vector of outcomes |
family |
Outcome type. Default is |
pl |
If TRUE Post-Lasso is used to estimate nuisance parameters, if FALSE Lasso |
cs |
If TRUE, common support will be checked |
q |
Quantile used for enforcing common support |
cl |
Vector with cluster variables can be provided |
print |
If TRUE, supporting information is printed |
se_rule |
If not NULL, define, e.g., c(-1,1) to get 1SE and 1SE+ rule |
w |
If TRUE, implied weights are calculated (only if pl=TRUE) |
parallel |
If TRUE, cross-validation of |
... |
Pass |
dmlmt
returns the results of the estimated average treatment effects and the potential outcomes. If specified, results of different SE rules and implied weights are returned.
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