neuralnet_complier_mod {DeepLearningCausal}

Train compliance model using neural networks

Description

Train model using group exposed to treatment with compliance as binary outcome variable and covariates.

Usage

neuralnet_complier_mod(
  complier.formula,
  exp.data,
  treat.var,
  algorithm = "rprop+",
  hidden.layer = c(4, 2),
  ID = NULL,
  stepmax = 1e+08
)

Arguments

complier.formula

formula for complier variable as outcome and covariates (c ~ x)

exp.data

data.frame for experimental data.

treat.var

string for treatment variable.

algorithm

string for algorithm for training neural networks. Default set to the Resilient back propagation with weight backtracking (rprop+). Other algorithms include backprop', rprop-', 'sag', or 'slr' (see neuralnet package).

hidden.layer

vector for specifying hidden layers and number of neurons.

ID

string for identifier variable

stepmax

maximum number of steps.

Value

trained complier model object