dmlRFapply: Double Machine Learning for Esitmating Treatment Effects

In mtvseven/DoubleDragon: What the Package Does (One Line, Title Case)

Description

This function performs the estimation of the debiased estimator as outlined in Chernozhukov et al (2016). It requres the user to provide a data frame, column indexes for the depenent and treatment variable, how many splits to perform, and whether to summarize the results or return all the output data in a list instead. The user also has a choice of how theta is calculated.

Usage

dmlRFapply(
  data = NULL,
  dep = NULL,
  treat = NULL,
  compile = TRUE,
  splits = 2,
  DML = "DML1"
)

Arguments

data	a data frame with depenent, treatment, and control variables.
dep	the column number of the dependent variable.
treat	the column number of the treatment variable.
compile	if TRUE, summarize the results.
splits	number of sample splits used to estimate treatment effect.
DML	1 - theta as calculated in equation 1.3 of Chernozhukov et al. (2016). 2 - theta as calculated in the footnotes on page 4 of Chernozhukov et al. (2016). 3 - theta using the Frisch-Waugh-Lovell style residual on residual regression.

Details

dmlRFapply differs from dmlRF in that the former fits the models to data splits using the apply method while the latter does so by looping through the splits.

Value

A named vector or list

Examples

dmlRF(data, dep = 1, treat = 2, splits = 3, DML = "FWL")

mtvseven/DoubleDragon documentation built on July 22, 2020, 10:57 a.m.