transfer from old repo

1 PA Decline/summaries.qmd

@@ -0,0 +1,109 @@
+---
+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)
+
+```