causens (version 0.0.3)

simulate_data: Generate data with unmeasured confounder

Description

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 = FALSE
)

Value

A data frame with the simulated dataset.

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

Unmeasured confounder coefficient in the propensity score model.

beta_uy

Unmeasured confounder coefficient in the outcome model.

treatment_effects

The treatment effect.

informative_u

A boolean indicating whether the unmeasured confounder is driven by covariates.