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

Generate data with a continuous unmeasured confounder and continuous outcome

Usage

gData_U_cont_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: Unmeasured confounder coefficient in the propensity score model.
beta_uy: Unmeasured confounder coefficient in the outcome model.
treatment_effects: The treatment effect.
seed: The seed for the random number generator.