neuralnet_pattc_counterfactuals: Assess Population Data counterfactuals

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

Assess Population Data counterfactuals

Description

Create counterfactual datasets in the population for compliers and noncompliers. Then predict potential outcomes using trained model from neuralnet_response_model.

Usage

neuralnet_pattc_counterfactuals(
  pop.data,
  neuralnet.response.mod,
  ID = NULL,
  cluster = NULL,
  binary.outcome = FALSE
)

Arguments

pop.data	population data.
neuralnet.response.mod	trained model from. neuralnet_response_model.
ID	string for identifier variable.
cluster	string for clustering variable (currently unused).
binary.outcome	logical specifying predicted outcome variable will take binary values or proportions.

Value

data.frame of predicted outcomes of response variable from counterfactuals.

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