PAPEcv | R Documentation |
This function estimates the Population Average Prescription Effect with and without a budget constraint. The details of the methods for this design are given in Imai and Li (2019).
PAPEcv(T, That, Y, ind, budget = NA, centered = TRUE)
T |
A vector of the unit-level binary treatment receipt variable for each sample. |
That |
A matrix where the |
Y |
The outcome variable of interest. |
ind |
A vector of integers (between 1 and number of folds inclusive) indicating which testing set does each sample belong to. |
budget |
The maximum percentage of population that can be treated under the budget constraint. Should be a decimal between 0 and 1. Default is NA which assumes no budget constraint. |
centered |
If |
A list that contains the following items:
pape |
The estimated Population Average Prescription Effect. |
sd |
The estimated standard deviation of PAPE. |
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)
That = matrix(c(0,1,1,0,0,1,1,0,1,0,0,1,1,0,0,1), nrow = 8, ncol = 2)
Y = c(4,5,0,2,4,1,-4,3)
ind = c(rep(1,4),rep(2,4))
papelist <- PAPEcv(T, That, Y, ind)
papelist$pape
papelist$sd
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