gData_U_binary_Y_binary: Generate data with a binary unmeasured confounder and binary...

In causens: Perform Causal Sensitivity Analyses Using Various Statistical Methods

Generate data with a binary unmeasured confounder and binary outcome

Description

Generate data with a binary unmeasured confounder and binary outcome

Usage

gData_U_binary_Y_binary(
  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.

Value

A data frame with the simulated dataset with U binary, Y binary.

causens documentation built on June 8, 2025, 10:03 a.m.