Generate data with unmeasured confounder
Usage
simulate_data(
ymodel = "linear",
N = 500,
u_type = "binary",
y_type = "continuous",
seed = 123,
alpha_uz = 0.2,
beta_uy = 0.5,
treatment_effects = 1,
informative_u = TRUE
)Arguments
- ymodel
A string indicating the functional form of the outcome model.
- N
The number of observations to be generated.
- u_type
A string indicating the type of the unmeasured confounder: "binary" or "continuous".
- y_type
A string indicating the type of the outcome: "binary" or "continuous".
- seed
The seed for the random number generator.
- 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.
- informative_u
A boolean indicating whether the unmeasured confounder is driven by covariates.