109 lines
2.6 KiB
Text
109 lines
2.6 KiB
Text
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---
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title: "Article A: Final renders"
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format: docx
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editor: visual
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---
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```{r}
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# ds <- readr::read_csv(here::here("/Volumes/Data/REDCap/DDV/talos_ddv.csv"))
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source(here::here("2 Longterm/data.R"))
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# The original functions from DST unedited
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source(here::here("1 PA Decline/Fra DDV/functions200411.R"))
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source(here::here("1 PA Decline/Fra DDV/functions240418.R"))
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# Modified functions to overwrite original
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source(here::here("R/functions.R"))
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```
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Files and resources used for article ready data:
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- "2 Longterm/data.R"
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- "R/functions240319.R"
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```{r}
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# ds |> finalfit::missing_plot()
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```
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On handling missings: https://finalfit.org/articles/missing.html
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```{r}
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# unique(df_long$variable)
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```
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```{r}
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pred_data <- df_ddv |>
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dplyr::tibble() |>
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dplyr::mutate_all(as.character) |>
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ready_clin() |>
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data_formatting() |>
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prediction_ready() |>
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dplyr::mutate(
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dplyr::across(
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c(
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tidyselect::starts_with("pase_"),
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"age"
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),
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as.numeric
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)
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)
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pred_data |> labelling_data() |> readr::write_rds("labelled_test.rds")
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skimr::skim(pred_data)
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wilcox.test(pred_data$pase_0, pred_data$pase_4, paired = TRUE)
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```
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```{r}
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pred_data |>
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true_pred_sum_plot() |>
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gtsummary::as_gt() |>
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# add_var_groups_gt()|>
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gt::gtsave(filename = here::here("1 PA Decline/table1.docx"))
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system2("open",here::here("'1 PA Decline/table1.docx'"))
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# gtsummary2docx(path=here::here("1 PA Decline/table1.docx"))
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```
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```{r}
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pred_data |>
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dplyr::mutate(reg_female = dplyr::if_else(reg_female, "Female", "Male")) |>
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pase_cutter(drop.pase = FALSE) |>
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dplyr::select(pase_change, dplyr::everything()) |>
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summary_tblone(by = "reg_female", missing = "no") |>
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gtsummary::modify_column_hide("stat_0") |>
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gtsummary::add_p() |>
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gtsummary::bold_p() |>
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micRo::mask_micro_summary() |>
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gtsummary::as_gt() |>
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gt::gtsave(filename = here::here("1 PA Decline/table_bysex.docx"))
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```
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```{r}
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skimr::skim(pred_data)
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```
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## Excluded patients
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```{r}
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df_ddv |>
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dplyr::tibble() |>
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dplyr::mutate_all(as.character) |>
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ready_clin() |>
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data_formatting()|>
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get_vars(c("clin","lifestyle","ses", "assess.pred")) |>
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dplyr::mutate(exclude=ifelse(is.na(pase_0)|is.na(pase_4),"Excluded","Included"),
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age=as.numeric(age),
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pase_0=as.numeric(pase_0),
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pase_4=as.numeric(pase_4)
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)|>
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# dplyr::select(-pase_0,-pase_4) |>
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#dplyr::select(exclude,soc_status_nowork, fam_indk_hl, edu_level_hl)|>
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gtsummary::tbl_summary(by=exclude, missing = "ifany") |>
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gtsummary::add_p() |>
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fix_labels() |>
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gtsummary::as_gt() |>
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gt::gtsave("1 PA Decline/summary_by_missing.docx")
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#|>
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# mask_micro_summary(micro.n = 5)
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```
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