Bayesian Estimation of ATE Subject to Unmeasured Confounding — causens_sf • causens

This function provides an estimate of the Average Treatment Effect (ATE) using Bayesian modelling.

Usage

causens_sf(fitted_model, exposure, outcome, data, bootstrap = FALSE, ...)

Arguments

fitted_model: The treatment model object as a glm.
exposure: The name of the exposure variable.
outcome: The name of the outcome variable.
data: A data frame containing the exposure, outcome, and confounder variables.
bootstrap: A logical indicating whether to perform bootstrap estimation of the 95% confidence interval.
...: Additional arguments to be passed to the sensitivity function.

Value

A point estimate of the corrected ATE.