estimate_cate {CRE} | R Documentation |
Estimate the Conditional Average Treatment Effect
Description
Estimates the Conditional Average Treatment Effect (CATE) by linearly modeling the Individual Treatment Effect by a set of rules.
Usage
estimate_cate(rules_matrix, rules_explicit, ite, B = 1, subsample = 1)
Arguments
rules_matrix |
A rules matrix. |
rules_explicit |
A list of select rules in terms of covariate names. |
ite |
The estimated ITEs. |
B |
The number of bootstrap samples for uncertainty quantification in estimation. |
subsample |
The bootstrap ratio subsample for uncertainty quantification in estimation. |
Value
A list with 2 elements:
summary
: A data frame summarizing the CATE linear decomposition:
-
Rule
: rule name, -
Estimate
: linear contribution to CATE, -
CI_lower
: lower bound 95% confidence interval on the estimate, -
CI_upper
: upper bound 95% confidence interval on the estimate, -
P_Value
: p-value (from Z-test).model
: A linear model for CATE-ATE estimation.
[Package CRE version 0.2.7 Index]