Run Gibbs sampler without covariates

Usage

prepost_gibbs_nocovar(
  formula,
  data,
  prepost,
  moderator,
  iter = 1000,
  thin = 1,
  burn = 0,
  monotonicity = TRUE,
  stable = TRUE,
  priors,
  predictive = FALSE
)

Arguments

formula: A formula with syntax y ~ t, where y is the name of the outcome variable and t is the name of the treatment.
data: A data frame containin the variables in the formula.
prepost: A one-sided formula with syntax ~ z, where z is the indicator variable for whether the moderator was measured pre- or post-treatment.
moderator: A formuala with syntax ~ d, where d is the moderator variable for the CATE.
iter: Numeric, number of iterations for the Gibbs
thin: Numeric, thinning parameter for the Gibbs
burn: Numeric, burn in rate for the Gibbs
monotonicity: A logical signifying whether Gibbs assumes monotonicity.
stable: A logical signifying whether Gibbs assumes stability.
priors: A list object containing the priors for the Gibbs sampler. Priors include beta.precision, psi.precision, alpha, y.alpha, and y.beta.
predictive: A logical indicator for whether to return prior predictive draws (TRUE) or posterior draws (FALSE, default).

Value

A list object containing Gibbs posterior quantities of interest and parameters.

Examples

x <- "alfa,bravo,charlie,delta"