AUPEC | R Documentation |
This function estimates AUPEC. The details of the methods for this design are given in Imai and Li (2019).
AUPEC(T, tau, Y, centered = TRUE)
T |
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 |
A list that contains the following items:
aupec |
The estimated Area Under Prescription Evaluation Curve |
sd |
The estimated standard deviation of AUPEC. |
vec |
A vector of points outlining the AUPEC curve across each possible budget point for the dataset. Each step increases the budget by 1/n where n is the number of data points. |
Michael Lingzhi Li, Technology and Operations Management, Harvard Business School mili@hbs.edu, https://www.michaellz.com/;
Imai and Li (2019). “Experimental Evaluation of Individualized Treatment Rules”,
T = 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(T,tau,Y)
aupeclist$aupec
aupeclist$sd
aupeclist$vec
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