AUPEC: Estimation of the Area Under Prescription Evaluation Curve (AUPEC) in Randomized Experiments
Description
This function estimates AUPEC. The details of the methods for this design are given in Imai and Li (2019).
Usage
AUPEC(Tr, tau, Y, centered = TRUE)
Arguments
Tr
A vector of the unit-level binary treatment receipt variable for each sample.
tau
A vector of the unit-level continuous score for treatment assignment. We assume those that have tau<0 should
not have treatment. Conditional Average Treatment Effect is one possible measure.
Y
A vector of the outcome variable of interest for each sample.
centered
If TRUE, the outcome variables would be centered before processing. This minimizes
the variance of the estimator. Default is TRUE.
Value
A list that contains the following items:
aupec
The estimated
Area Under Prescription Evaluation Curve
sd
The estimated standard deviation
of AUPEC.
References
Imai and Li (2019). “Experimental Evaluation of Individualized Treatment Rules”,
# NOT RUN {Tr = c(1,0,1,0,1,0,1,0)
tau = c(0,0.1,0.2,0.3,0.4,0.5,0.6,0.7)
Y = c(4,5,0,2,4,1,-4,3)
aupeclist <- AUPEC(Tr,tau,Y)
aupeclist$aupec
aupeclist$sd
# }