---
title: "Article A: Final renders"
format: docx
editor: visual
---

```{r}
# ds <- readr::read_csv(here::here("/Volumes/Data/REDCap/DDV/talos_ddv.csv"))
source(here::here("2 Longterm/data.R"))
# The original functions from DST unedited
source(here::here("1 PA Decline/Fra DDV/functions200411.R"))
source(here::here("1 PA Decline/Fra DDV/functions240418.R"))
# Modified functions to overwrite original
source(here::here("R/functions.R"))
```

Files and resources used for article ready data:

-   "2 Longterm/data.R"

-   "R/functions240319.R"

```{r}
# ds |> finalfit::missing_plot()
```

On handling missings: https://finalfit.org/articles/missing.html

```{r}
# unique(df_long$variable)
```

```{r}
pred_data <- df_ddv |>
  dplyr::tibble() |>
  dplyr::mutate_all(as.character) |>
  ready_clin() |>
  data_formatting() |>
  prediction_ready() |>
  dplyr::mutate(
    dplyr::across(
      c(
        tidyselect::starts_with("pase_"),
        "age"
      ),
      as.numeric
    )
  )

pred_data |> labelling_data() |> readr::write_rds("labelled_test.rds")

skimr::skim(pred_data)

wilcox.test(pred_data$pase_0, pred_data$pase_4, paired = TRUE)
```

```{r}
pred_data |>
  true_pred_sum_plot() |>
  gtsummary::as_gt() |>
  # add_var_groups_gt()|>
  gt::gtsave(filename = here::here("1 PA Decline/table1.docx"))
system2("open",here::here("'1 PA Decline/table1.docx'"))
# gtsummary2docx(path=here::here("1 PA Decline/table1.docx"))
```

```{r}
pred_data |>
  dplyr::mutate(reg_female = dplyr::if_else(reg_female, "Female", "Male")) |>
  pase_cutter(drop.pase = FALSE) |>
  dplyr::select(pase_change, dplyr::everything()) |>
  summary_tblone(by = "reg_female", missing = "no") |>
  gtsummary::modify_column_hide("stat_0") |>
  gtsummary::add_p() |>
  gtsummary::bold_p() |>
  micRo::mask_micro_summary() |>
  gtsummary::as_gt() |>
  gt::gtsave(filename = here::here("1 PA Decline/table_bysex.docx"))
```

```{r}
skimr::skim(pred_data)
```

## Excluded patients

```{r}
df_ddv |>
  dplyr::tibble() |>
  dplyr::mutate_all(as.character) |>
  ready_clin() |>
  data_formatting()|>
  get_vars(c("clin","lifestyle","ses", "assess.pred"))  |> 
  dplyr::mutate(exclude=ifelse(is.na(pase_0)|is.na(pase_4),"Excluded","Included"),
                age=as.numeric(age),
                pase_0=as.numeric(pase_0),
                pase_4=as.numeric(pase_4)
                )|> 
  # dplyr::select(-pase_0,-pase_4)  |> 
  #dplyr::select(exclude,soc_status_nowork, fam_indk_hl, edu_level_hl)|> 
  gtsummary::tbl_summary(by=exclude, missing = "ifany") |> 
  gtsummary::add_p() |> 
  fix_labels() |> 
  gtsummary::as_gt() |> 
  gt::gtsave("1 PA Decline/summary_by_missing.docx")
#|> 
 # mask_micro_summary(micro.n = 5)

```