Description Usage Arguments Value References
This function implements inverse probability weighted (IPW) estimation of average treatment effects (ATEs), provided fitted propensity scores.
1 | ate.ipw(y, tr, mfp)
|
y |
An n x 1 vector of observed outcomes. |
tr |
An n x 1 vector of treatment indicators (=1 if treated or 0 if untreated). |
mfp |
An n x 2 matrix of fitted propensity scores for untreated (first column) and treated (second column). |
one |
The direct IPW estimates of 1. |
est |
The ratio IPW estimates of means. |
diff |
The ratio IPW estimate of ATE. |
Tan, Z. (2020a) Regularized calibrated estimation of propensity scores with model misspecification and high-dimensional data, Biometrika, 107, 137<e2><80><93>158.
Tan, Z. (2020b) Model-assisted inference for treatment effects using regularized calibrated estimation with high-dimensional data, Annals of Statistics, 48, 811<e2><80><93>837.
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