R/data-recover.r

In KatoPachi/discreteRD: What the Package Does (One Line, Title Case)

#' Recover Data from estimation object
#'
#' @param object estimation object
#' @param \dots other arguments
#' @export
#'
recover_data <- function(object, ...) {
  UseMethod("recover_data")
}

#'
#' @name recover_data
#' @param modnum numeric. which model you use.
#' @export
#'
recover_data.list_global_lm <- function(object, modnum, ...) {
  # result list
  use_result <- object$result[[modnum]]

  # control and treated data
  d0 <- cbind(
    use_result$control$input$response,
    use_result$control$input$design,
    weights = use_result$control$input$weights,
    d = 0
  )

  d1 <- cbind(
    use_result$treat$input$response,
    use_result$treat$input$design,
    weights = use_result$treat$input$weights,
    d = 1
  )

  xlab <- colnames(use_result$control$input$design)
  d <- data.frame(rbind(d0, d1))
  colnames(d) <- c("outcome", xlab, "weights", "d")
  d
}

#'
#' @name recover_data
#' @export
#'
recover_data.list_local_lm <- function(object, modnum, ...) {
  d <- recover_data.list_global_lm(object, modnum)
  res <- object$result[[modnum]]

  d$kweight <- c(
    res$control$input$local.wls$kernel.w,
    res$treat$input$local.wls$kernel.w
  )

  if (!is.null(res$treat$input$local.wls$given.w)) {
    d$sweight <- c(
      res$control$input$local.wls$given.w,
      res$treat$input$local.wls$given.w
    )
  } else {
    d$sweight <- 1
  }

  d
}