grade as factor in ae_plot_grade_max

participate in #35

NAMESPACE

@@ -112,6 +112,7 @@ importFrom(ggplot2,scale_fill_steps)
 importFrom(ggplot2,scale_x_continuous)
 importFrom(ggplot2,scale_x_discrete)
 importFrom(ggplot2,scale_y_continuous)
+importFrom(ggplot2,scale_y_discrete)
 importFrom(ggplot2,theme)
 importFrom(ggplot2,unit)
 importFrom(ggplot2,vars)

R/ae_table_grade.R

@@ -67,10 +67,11 @@ ae_table_grade_max = function(
 #' @inheritParams ae_table_soc 
 #' @inherit ae_table_soc seealso
 #' @param type the plots to be included. One of `c("stack", "dodge", "fill")`.
+#' @param drop_levels whether to drop unused grade levels.
 #'
 #' @return a patchwork of ggplots
 #' @importFrom dplyr arrange full_join mutate rename_with select summarise
-#' @importFrom ggplot2 aes geom_bar ggplot labs scale_x_continuous theme waiver
+#' @importFrom ggplot2 aes geom_bar ggplot labs scale_x_continuous scale_y_discrete theme waiver
 #' @importFrom purrr map
 #' @importFrom rlang set_names
 #' @export
@@ -88,6 +89,7 @@ ae_table_grade_max = function(
 ae_plot_grade_max = function(
  df_ae, ..., df_enrol, 
  type = c("stack", "dodge", "fill"),
+ drop_levels = FALSE,
  arm="ARM", subjid="SUBJID", soc="AESOC", grade="AEGR"
 ){
  check_installed("patchwork", "for `ae_plot_grade_max()` to work")
@@ -99,25 +101,21 @@ ae_plot_grade_max = function(
  select(subjid=any_of2(subjid), arm=any_of2(arm)) %>%
  full_join(df_ae, by="subjid") %>% 
  arrange(subjid) %>% 
- mutate(grade = ifelse(is.na(soc), 0, fix_grade(grade)) %>% recode("Grade 0"="No AE"))
+ mutate(grade = ifelse(is.na(soc), 0, fix_grade(grade)))
 
- if(is.null(arm)){
- x = a %>% 
- summarise(grade_max = max_narm(grade), .by=c(subjid)) %>% 
- mutate(grade_max = ifelse(is.na(grade_max), "NA", paste("Grade", grade_max)))
- } else {
- x = a %>% 
- summarise(grade_max = max_narm(grade), .by=c(subjid, arm)) %>% 
- mutate(grade_max = ifelse(is.na(grade_max), "NA", paste("Grade", grade_max)))
- }
+ by_cols = if(is.null(arm)) "subjid" else c("subjid", "arm")
+ x = a %>% 
+ summarise(grade_max = max_narm(grade), .by=any_of(by_cols)) %>% 
+ mutate(grade_max = factor(grade_max, levels=0:5, labels=c("No AE", paste("Grade", 1:5))))
 
  if(is.null(arm)) type="stack"
  p_list = type %>% set_names() %>% 
  map(~{
  y_lab = if(.x=="fill") "Proportion" else "Count"
  p = x %>% 
- ggplot(aes(y=grade_max, fill=arm, by=factor(grade_max))) +
+ ggplot(aes(y=grade_max, fill=arm, by=grade_max)) +
  geom_bar(position=.x) +
+ scale_y_discrete(drop=drop_levels) +
  scale_x_continuous(labels = if(.x=="fill") scales::percent else waiver()) +
  labs(y="Max AE grade experienced", x=y_lab, fill="Treatment")
  # StatProp = ggstats:::StatProp
@@ -202,7 +200,7 @@ ae_table_grade_n = function(
  p = crosstable::format_fixed(x/tot, digits, percent=TRUE)
  paste0(x, " (", p, ")")
  }))
- attr(rtn, "by_table")[] = npat[names(npat)!="Total"]
+ attr(rtn, "by_table")[] = npat[!is.na(names(npat)) & names(npat)!="Total"] #zarb que crosstable oublie les NA dans by_table non?
  rtn
 }