targets::tar_read("df_all_data_formatted") |>
  events_ready() |>
  dplyr::filter(!is.na(pase_0), !is.na(pase_4)) |>
  (\(data){
    c("pase_0", "pase_4") |>
      purrr::map(\(exp){
        list(
          "Univariable" = cox_regression(data = data, all.vars = FALSE, use.strata = FALSE, outcome.var = exp),
          "Multivariable" = cox_regression(data = data, all.vars = TRUE, use.strata = FALSE, outcome.var = exp)
        ) |>
          purrr::map(\(.x){
            .x |>
              gtsummary::tbl_regression(exponentiate = TRUE) |>
              fix_labels()
          }) |>
          tbl_merged_named()
      })
  })() |>
  gtsummary::tbl_stack()


targets::tar_read("df_all_data_formatted") |>
  pase_cutter(drop.nas = TRUE) |>
  events_ready(v.groups = c("clin", "lifestyle.events", "ses", "assess.events", "quartiles")) |>
  dplyr::select(-dplyr::any_of(c("pase_0", "pase_4", "pase_change"))) |>
  (\(data){
    c("pase_0_quartile", "pase_4_quartile") |>
      purrr::map(\(exp){
        list(
          "Univariable" = cox_regression(data = data, all.vars = FALSE, use.strata = FALSE, outcome.var = exp),
          "Multivariable" = cox_regression(data = data, all.vars = TRUE, use.strata = FALSE, outcome.var = exp)
        ) |>
          purrr::map(\(.x){
            .x |>
              gtsummary::tbl_regression(exponentiate = TRUE) |>
              fix_labels()
          }) |>
          tbl_merged_named()
      })
  })() |>
  gtsummary::tbl_stack()


targets::tar_read("df_all_data_formatted") |>
  pase_cutter(drop.nas = TRUE) |>
  get_vars(vars.groups = c("clin", "lifestyle.events", "ses", "assess.events", "quartiles"), vars.vec = c("inc_time")) |>
  dplyr::mutate(time = time + inc_time / 365) |>
  dplyr::select(-dplyr::any_of(c("pase_0", "pase_4", "pase_change", "inc_time", "event.include", "pase_4_quartile"))) |>
  (\(data){
    list(
      "Univariable" = cox_regression(data = data, all.vars = FALSE, use.strata = FALSE, outcome.var = "pase_0_quartile"),
      "Multivariable" = cox_regression(data = data, all.vars = TRUE, use.strata = FALSE, outcome.var = "pase_0_quartile")
    ) |>
      purrr::map(\(.x){
        .x |>
          gtsummary::tbl_regression(exponentiate = TRUE) |>
          fix_labels()
      }) |>
      tbl_merged_named()
  })()

ls_sens <- list(
  pase_0_all_quartile = list(
    data = targets::tar_read("df_all_data_formatted") |>
      pase_cutter(drop.nas = FALSE) |>
      get_vars(vars.groups = c("clin", "lifestyle.events", "ses", "assess.pred", "quartiles"), vars.vec = c("inc_time",
                                                                                                            "time",
                                                                                                            "status")) |>
      dplyr::mutate(time = time + inc_time / 365) |>
      dplyr::select(-dplyr::any_of(c("pase_0", "pase_4", "pase_change", "inc_time", "event.include", "pase_4_quartile"))),
    main.exp = "pase_0_quartile"
  ),
  # pase_0_all_contin = list(
  #   data = targets::tar_read("df_all_data_formatted") |>
  #     get_vars(vars.groups = c("clin", "lifestyle.events", "ses", "assess.pred", "quartiles"), vars.vec = c("inc_time",
  #                                                                                                           "time",
  #                                                                                                           "status")) |>
  #     dplyr::mutate(time = time + inc_time / 365) |>
  #     dplyr::select(-dplyr::any_of(c("pase_4", "pase_change", "inc_time", "event.include", "pase_0_quartile", "pase_4_quartile"))),
  #   main.exp = "pase_0"
  # ),
  pase_0_excl_quartile = list(
    data = targets::tar_read("df_all_data_formatted") |>
      pase_cutter(drop.nas = TRUE,drop.pase = FALSE) |>
      events_ready(v.groups = c("clin", "lifestyle.events", "ses", "assess.pred", "quartiles"), vars.vec = c("inc_time",
                                                                                                             "time",
                                                                                                             "status")) |>
      dplyr::select(-dplyr::any_of(c("pase_0","pase_4", "pase_change", "inc_time", "event.include", "pase_4_quartile"))),
    main.exp = "pase_0_quartile"
  ),
  # pase_0_excl_contin = list(
  #   data = targets::tar_read("df_all_data_formatted") |>
  #     events_ready(v.groups = c("clin", "lifestyle.events", "ses", "assess.pred", "quartiles"), vars.vec = c("inc_time",
  #                                                                                                            "time",
  #                                                                                                            "status")) |>
  #     dplyr::filter(!is.na(pase_0), !is.na(pase_4)) |>
  #     dplyr::select(-pase_4),
  #   main.exp = "pase_0"
  # ),
  pase_4_quartile = list(
    data = targets::tar_read("df_all_data_formatted") |>
      dplyr::mutate(pase_4_quartile=cut(x = pase_4, breaks = quantile(pase_4, na.rm = TRUE), labels = 1:4, include.lowest = TRUE))  |>
      get_vars(vars.groups = c("clin", "lifestyle.events", "ses", "assess.events", "quartiles"))|>
      dplyr::filter(!is.na(pase_4_quartile),event.include) |>
      dplyr::select(-dplyr::any_of(c("pase_0","pase_4", "pase_change", "inc_time", "event.include", "pase_0_quartile"))),
    main.exp = "pase_4_quartile"
  ),
  # pase_4_contin = list(
  #   data = targets::tar_read("df_all_data_formatted") |>
  #     events_ready() |>
  #     dplyr::filter(!is.na(pase_0), !is.na(pase_4)) |>
  #     dplyr::select(-pase_0),
  #   main.exp = "pase_4"
  # ),
  pase_4_change_late_cut = list(
    data = targets::tar_read("df_all_data_formatted") |>
      events_ready() |>
      dplyr::filter(!is.na(pase_0), !is.na(pase_4)) |>
      pase_cutter(drop.pase = TRUE),
    main.exp = "pase_change"
  # ),
  # pase_4_change_earliest_cut = list(
  #   data = targets::tar_read("df_all_data_formatted") |>
  #     pase_cutter(drop.pase = TRUE)|>
  #     events_ready(vars.vec = c("pase_change")) |>
  #     dplyr::filter(!is.na(pase_change)) ,
  #   main.exp = "pase_change"
  )
)



f <- function(data, main.exp, ...) {
  set.seed(3023)
  imp <- fun_impute(data = data, ignore = main.exp)

  list(
    "Univariable" = cox_regression(data = data, all.vars = FALSE, use.strata = FALSE, outcome.var = main.exp),
    "Multivariable" = cox_regression(data = data, all.vars = TRUE, use.strata = FALSE, outcome.var = main.exp),
    "Multivariable Imputed" = cox_regression(data = imp, all.vars = TRUE, use.strata = FALSE, outcome.var = main.exp)
  )
}


ls_out <- purrr::map(ls_sens, \(.x){
  do.call(f, .x)
})

ls_stack <- ls_out |>
  purrr::imap(\(.x, .i){
    list(
      "Group counts" = ls_sens[[.i]][["data"]] |>
        dplyr::select(ls_sens[[.i]][["main.exp"]]) |> 
        gtsummary::tbl_summary(statistic =  list(gtsummary::all_continuous() ~ "{N_nonmiss} ({p_nonmiss}%)", gtsummary::all_categorical() ~ "{n} ({p}%)")) |> 
        fix_labels(),
      .x |>
        lapply(\(.y){
          .y |>
            tbl_regression_standard() |>
            # gtsummary::modify_table_styling(columns = tidyselect::starts_with("p.value"), hide = TRUE) |>
            gtsummary::remove_row_type(variables = -dplyr::any_of(ls_sens[[.i]][["main.exp"]]), type = "all") |> 
            gtsummary::bold_p()
        })
    ) |>
      purrr::list_flatten() |>
      tbl_merged_named()
  }) |>
  tbl_stack_named()

ls_stack <- ls_stack|> gtsummary::as_gt() |> gt::tab_style(style = gt::cell_text(weight="bold"),locations = gt::cells_row_groups(dplyr::everything()))

ls_stack |> gt::gtsave(filename = here::here("out/pase_extra_cox2.docx"))