## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
library(dceasimR)

## ----step1--------------------------------------------------------------------
# Check whether disease has SES gradient
# Use disease_icd to auto-lookup HES utilisation
result <- run_aggregate_dcea(
  icer            = 28000,
  inc_qaly        = 0.45,
  inc_cost        = 12600,
  population_size = 12000,
  disease_icd     = "C34",
  wtp             = 20000,
  opportunity_cost_threshold = 13000
)

## ----step2--------------------------------------------------------------------
sa <- run_dcea_sensitivity(result, params_to_vary = c("eta", "wtp", "occ_threshold"))
sa$eta_profile

## ----step3--------------------------------------------------------------------
tbl <- generate_nice_table(result, format = "tibble")
knitr::kable(tbl, caption = "DCEA Summary Table (NICE format)")

## ----step4, eval = FALSE------------------------------------------------------
# export_dcea_excel(result, "dcea_submission.xlsx")

## ----step5, fig.width = 6, fig.height = 5-------------------------------------
plot_equity_impact_plane(result)