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#' Add Net Interventions Avoided
#'
#' Add the number of net interventions avoided to `dca()` object.
#'
#' @param x object of class `'dca'` calculated with `dca()`
#' @param nper Number to report net interventions per. Default is 1
#'
#' @return 'dca' object
#' @export
#' @author Daniel D Sjoberg
#' @seealso [`dca()`], [`standardized_net_benefit()`], [`plot.dca()`], [`as_tibble.dca()`]
#'
#' @examples
#' dca(
#' cancer ~ cancerpredmarker,
#' data = df_binary
#' ) %>%
#' net_intervention_avoided()
#'
#' dca(
#' Surv(ttcancer, cancer) ~ cancerpredmarker,
#' data = df_surv,
#' time = 1
#' ) %>%
#' net_intervention_avoided(nper = 100)
net_intervention_avoided <- function(x, nper = 1) {
if (!inherits(x, "dca")) {
stop("Argument `x=` must be class 'dca' calculated with `dca()`",
call. = FALSE
)
}
x$dca <-
x$dca %>%
dplyr::left_join(
dplyr::filter(., .data$variable %in% "all") %>%
dplyr::select("threshold", net_benefit_all = "net_benefit"),
by = "threshold"
) %>%
dplyr::mutate(
net_intervention_avoided =
(.data$net_benefit - .data$net_benefit_all) /
(.data$threshold / (1 - .data$threshold)) * .env$nper
) %>%
dplyr::select(-"net_benefit_all")
# add nper info to dca list --------------------------------------------------
x$net_interventions_nper <- nper
# return dca object ----------------------------------------------------------
x
}
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