vt2_ctree: Estimate the CATE using a conditional inference tree for Step...
In jackmwolf/tehtuner: Fit and Tune Models to Detect Treatment Effect Heterogeneity
vt2_ctree R Documentation
Estimate the CATE using a conditional inference tree for Step 2
Description
Estimate the CATE using a conditional inference tree for Step 2
Usage
vt2_ctree(z, data, Trt, Y, theta)
Arguments
z
a numeric vector of estimated CATEs from Step 1
data
a data frame containing a response, binary treatment indicators,
and covariates.
Trt
a string specifying the name of the column of data
contains the treatment indicators.
Y
a string specifying the name of the column of data
contains the response.
theta
the value of the test statistic that must be exceeded in order
to implement a split (mincriterion)
Value
An object of class BinaryTree-class. See
BinaryTree-class.
See Also
Other VT Step 2 functions:
vt2_classtree(),
vt2_lasso(),
vt2_rtree()
jackmwolf/tehtuner documentation built on June 10, 2025, 10:32 p.m.
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| vt2_ctree | R Documentation |
Estimate the CATE using a conditional inference tree for Step 2
Description
Estimate the CATE using a conditional inference tree for Step 2
Usage
vt2_ctree(z, data, Trt, Y, theta)
Arguments
z |
a numeric vector of estimated CATEs from Step 1 |
data |
a data frame containing a response, binary treatment indicators, and covariates. |
Trt |
a string specifying the name of the column of |
Y |
a string specifying the name of the column of |
theta |
the value of the test statistic that must be exceeded in order
to implement a split ( |
Value
An object of class BinaryTree-class. See
BinaryTree-class.
See Also
Other VT Step 2 functions:
vt2_classtree(),
vt2_lasso(),
vt2_rtree()
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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