#' combine_popmod_dectree_res
#'
#' Combine cost and QALY outputs from decision tree model and population model
#' for overall cost-effectiveness samples.
#'
#' @param cohort individual level data; dataframe
#' @param interv fixed model run inputs; list
#' @param popmod_res output of \code{activetb_qaly_cost()}; list
#' @param dectree_res output of \code{parallel_decision_tree()}; list
#' @param folders list of ouput folder locations
#'
#' @return list of cost-effective statistics:
#' \itemize{
#' \item ce0: marginal status-quo. Costs and QALYs of each sim.
#' \item ce1: marginal intervention. Costs and QALYs of each sim.
#' \item ce_default: non-incremental cost-effectiveness i.e. dataframe with first column status-quo.
#' \item ce_incr: incremental cost-effectivness i.e. dataframe with first column 0 and other screening cost minus status-quo.
#' }
#' @export
#' @seealso
#' \code{\link{parallel_decision_tree}},
#' \code{\link{activetb_qaly_cost}}
#'
#' @examples
#'
combine_popmod_dectree_res <- function(cohort,
interv,
popmod_res,
dectree_res,
folders = NA) {
t_dectree <- list(cost_person = purrr::map(dectree_res, "mc_cost"),
QALY_person = purrr::map(dectree_res, "mc_health"))
screen_discount <- screen_discount(cohort,
interv$discount_rate)
ce_incr <- make_incremental_ce(popmod_res,
t_dectree,
screen_discount,
folders)
ce0 <- make_ce0(popmod_res)
ce1 <- make_ce1(popmod_res,
t_dectree,
screen_discount)
ce_default <- ce_default(ce0, ce1)
ce_res <- list(
ce0 = ce0,
ce1 = ce1,
ce_default = ce_default,
ce_incr = ce_incr)
save(ce_res, file = pastef(folders$output$scenario, "ce_res.RData"))
return(ce_res)
}
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