Generate data with a binary unmeasured confounder and continuous outcome — gData_U_binary_Y_cont • causens

Generate data with a binary unmeasured confounder and continuous outcome

Usage

gData_U_binary_Y_cont(
  ymodel = "linear",
  N = 500,
  alpha_uz = 0.2,
  beta_uy = 0.5,
  treatment_effects = 1,
  seed = 123
)

Arguments

ymodel: A string indicating the functional form of the outcome model.
N: The number of observations to be generated.
alpha_uz: The coefficient of the unmeasured confounder in the propensity score model.
beta_uy: The coefficient of the unmeasured confounder in the outcome model.
treatment_effects: The treatment effect.
seed: The seed for the random number generator.

Examples

fulldata <- gData_U_binary_Y_cont(
  ymodel = "linear",
  N = 500,
  alpha_uz = 0.2,
  beta_uy = 0.5,
  treatment_effects = 1,
  seed = 123
)
table(fulldata$Z)
#> 
#>   0   1 
#> 238 262