response_model: Response model from experimental data using SL ensemble

In DeepLearningCausal: Causal Inference with Super Learner and Deep Neural Networks

Response model from experimental data using SL ensemble

Description

Train response model (response variable as outcome and covariates) from all compliers (actual + predicted) in experimental data using SL ensemble.

Usage

response_model(
  response.formula,
  exp.data,
  compl.var,
  exp.compliers,
  family = "binomial",
  ID = NULL,
  SL.learners = c("SL.glmnet", "SL.xgboost", "SL.ranger", "SL.nnet", "SL.glm")
)

Arguments

response.formula	formula to fit the response model (y ~ x) using binary outcome variable and covariates
exp.data	experimental dataset.
compl.var	string specifying binary complier variable
exp.compliers	data.frame object of compliers from complier_predict.
family	string for "gaussian" or "binomial".
ID	string for identifier variable.
SL.learners	vector of names of ML algorithms used for ensemble model.

Value

trained response model.

DeepLearningCausal documentation built on Sept. 11, 2024, 8:40 p.m.