R/summary.CIMTx_ATE_posterior.R

In CIMTx: Causal Inference for Multiple Treatments with a Binary Outcome

#' Summarize a CIMTx_ATE_posterior object
#'
#' @param object a \code{CIMTx_ATE_posterior} object
#' obtained with \code{\link{ce_estimate}} function.
#' @param ... further arguments passed to or from other methods.
#'
#' @return a list with w*(w-1)/2 elements for ATE effect.
#' Each element of the list contains the estimation,
#' standard error, lower and upper 95\% CI for RD/RR/OR.
#' @importFrom stringr str_detect str_sub
#' @export
#'
#' @references
#' Hadley Wickham (2019).
#' \emph{stringr: Simple, Consistent Wrappers for Common String Operations}.
#' R package version 1.4.0.
#' URL:\url{https://CRAN.R-project.org/package=stringr}
#'
#' @examples
#' library(CIMTx)
#' lp_w_all <-
#'   c(
#'     ".4*x1 + .1*x2  - .1*x4 + .1*x5", # w = 1
#'     ".2 * x1 + .2 * x2  - .2 * x4 - .3 * x5"
#'   ) # w = 2
#' nlp_w_all <-
#'   c(
#'     "-.5*x1*x4  - .1*x2*x5", # w = 1
#'     "-.3*x1*x4 + .2*x2*x5"
#'   ) # w = 2
#' lp_y_all <- rep(".2*x1 + .3*x2 - .1*x3 - .1*x4 - .2*x5", 3)
#' nlp_y_all <- rep(".7*x1*x1  - .1*x2*x3", 3)
#' X_all <- c(
#'   "rnorm(0, 0.5)", # x1
#'   "rbeta(2, .4)", # x2
#'   "runif(0, 0.5)", # x3
#'   "rweibull(1,2)", # x4
#'   "rbinom(1, .4)" # x5
#' )
#'
#' set.seed(111111)
#' data <- data_sim(
#'   sample_size = 300,
#'   n_trt = 3,
#'   x = X_all,
#'   lp_y = lp_y_all,
#'   nlp_y = nlp_y_all,
#'   align = FALSE,
#'   lp_w = lp_w_all,
#'   nlp_w = nlp_w_all,
#'   tau = c(-1.5, 0, 1.5),
#'   delta = c(0.5, 0.5),
#'   psi = 1
#' )
#' ce_estimate_ra_ate_result <- ce_estimate(
#'   y = data$y, x = data$covariates,
#'   w = data$w, ndpost = 10, method = "RA", estimand = "ATE"
#' )
#' summary(ce_estimate_ra_ate_result)
summary.CIMTx_ATE_posterior <- function(object, ...) {
  object <- object[stringr::str_detect(names(object), "ATE")]
  n_trt <-
    length(unique(as.integer(stringr::str_sub(
      names(object), 8, 8
    )))) + 1
  result_summary <- NULL
  for (i in 1:(n_trt - 1)) {
    for (j in (i + 1):n_trt) {
      assign(paste0("ate", i, j),
             posterior_summary(object[[paste0("ATE_RD", i, j)]],
                               object[[paste0("ATE_RR", i, j)]],
                               object[[paste0("ATE_OR", i, j)]]))
      assign(paste0("ATE", i, j), list(round(eval(
        parse(text = (paste0("ate", i, j)))
      ), digits = 2)))
      assign(paste0("ATE", i, j), stats::setNames(eval(parse(
        text = (paste0("ATE", i, j))
      )), paste0("ATE", i, j)))
      result_summary <-
        c(result_summary, (eval(parse(
          text = (paste0("ATE", i, j))
        ))))
    }
  }
  return(result_summary)
}