get_mnpp {tehtuner}

Get the MNPP for the Step 2 model

Description

Find the lowest penalty parameter so that the Step 2 model fit for the estimated CATE from Step 1 is constant for all subjects.

Usage

get_mnpp(z, data, step2, Trt, Y, threshold)

Arguments

z

a numeric vector of estimated CATEs from Step 1

data

a data frame containing a response, binary treatment indicators, and covariates.

step2

a character string specifying the Step 2 model. Supports "lasso", "rtree", "classtree", or "ctree".

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.

threshold

for "step2 = 'classtree'" only. The value against which to test if the estimated individual treatment effect from Step 1 is higher (TRUE) or lower (FALSE).