tm_t_shift_by_grade.md
In teal.modules.clinical: 'teal' Modules for Standard Clinical Outputs

template_shift_by_grade generates correct expressions with default arguments

Code
  res
Output
  $data
  {
      anl <- adlb %>% dplyr::filter(WGRLOVFL == "Y")
      anl <- anl %>% dplyr::mutate(ARM = droplevels(ARM))
      arm_levels <- levels(anl[["ARM"]])
      adsl <- adsl %>% dplyr::filter(ARM %in% arm_levels)
      adsl <- adsl %>% dplyr::mutate(ARM = droplevels(ARM))
      anl <- df_explicit_na(anl, na_level = "<Missing>")
      adsl <- df_explicit_na(adsl, na_level = "<Missing>")
      by_visit <- TRUE
      anl <- dplyr::mutate(anl, ATOXGR_GP = factor(dplyr::case_when(ATOXGR %in% 
          c(0, 1, 2, 3, 4) ~ "Not Low", ATOXGR == -1 ~ "1", ATOXGR == 
          -2 ~ "2", ATOXGR == -3 ~ "3", ATOXGR == -4 ~ "4", ATOXGR == 
          "<Missing>" ~ "Missing")), BTOXGR_GP = factor(dplyr::case_when(BTOXGR %in% 
          c(0, 1, 2, 3, 4) ~ "Not Low", BTOXGR == -1 ~ "1", BTOXGR == 
          -2 ~ "2", BTOXGR == -3 ~ "3", BTOXGR == -4 ~ "4", BTOXGR == 
          "<Missing>" ~ "Missing")))
      anl <- dplyr::mutate(anl, ATOXGR_GP = factor(ATOXGR_GP, levels = c(dplyr::if_else("WGRLOVFL" %in% 
          c("WGRLOVFL", "WGRLOFL"), "Not Low", "Not High"), "1", 
          "2", "3", "4", "Missing")), BTOXGR_GP = factor(BTOXGR_GP, 
          levels = c(dplyr::if_else("WGRLOVFL" %in% c("WGRLOVFL", 
              "WGRLOFL"), "Not Low", "Not High"), "1", "2", "3", 
              "4", "Missing")))
      column_labels <- list(PARAMCD = teal.data::col_labels(anl, 
          fill = FALSE)[["PARAMCD"]], AVISIT = teal.data::col_labels(anl, 
          fill = FALSE)[["AVISIT"]], ATOXGR_GP = dplyr::if_else(TRUE, 
          "Grade at Visit", "Post-baseline Grade"), BTOXGR_GP = "Baseline Grade")
      teal.data::col_labels(anl)[names(column_labels)] <- as.character(column_labels)
      anl
  }

  $layout_prep
  split_fun <- drop_split_levels

  $layout
  lyt <- rtables::basic_table(title = "Grade Summary Table", subtitles = "Worst Flag Variable: WGRLOVFL", 
      show_colcounts = TRUE) %>% rtables::split_cols_by(var = "ARM") %>% 
      rtables::split_rows_by(var = "PARAMCD", split_fun = split_fun, 
          label_pos = "topleft", split_label = teal.data::col_labels(anl, 
              fill = FALSE)[["PARAMCD"]]) %>% rtables::split_rows_by("AVISIT", 
      split_fun = split_fun, label_pos = "topleft", split_label = teal.data::col_labels(anl, 
          fill = FALSE)[["AVISIT"]]) %>% rtables::split_rows_by(var = "ATOXGR_GP", 
      split_fun = split_fun, label_pos = "topleft", split_label = teal.data::col_labels(anl, 
          fill = FALSE)[["ATOXGR_GP"]]) %>% summarize_num_patients(var = "USUBJID", 
      .stats = c("unique_count")) %>% count_occurrences(vars = "BTOXGR_GP", 
      denom = "n", drop = TRUE, .indent_mods = 4L) %>% append_varlabels(anl, 
      "BTOXGR_GP", indent = 3L)

  $table
  {
      table <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = adsl) %>% 
          rtables::prune_table()
  }

template_shift_by_grade generates correct expressions with custom arguments

Code
  res
Output
  $data
  {
      anl <- adlb %>% dplyr::filter(WGRLOVFL == "YY")
      anl <- anl %>% dplyr::mutate(ARM = droplevels(ARM))
      arm_levels <- levels(anl[["ARM"]])
      adsl <- adsl %>% dplyr::filter(ARM %in% arm_levels)
      adsl <- adsl %>% dplyr::mutate(ARM = droplevels(ARM))
      anl <- df_explicit_na(anl, na_level = "<MYMissing>")
      adsl <- df_explicit_na(adsl, na_level = "<MYMissing>")
      by_visit <- TRUE
      anl <- dplyr::mutate(anl, ATOXGR_GP = factor(dplyr::case_when(MYATOXGR %in% 
          c(0, 1, 2, 3, 4) ~ "Not Low", MYATOXGR == -1 ~ "1", MYATOXGR == 
          -2 ~ "2", MYATOXGR == -3 ~ "3", MYATOXGR == -4 ~ "4", 
          MYATOXGR == "<MYMissing>" ~ "Missing")), BTOXGR_GP = factor(dplyr::case_when(MYBTOXGR %in% 
          c(0, 1, 2, 3, 4) ~ "Not Low", MYBTOXGR == -1 ~ "1", MYBTOXGR == 
          -2 ~ "2", MYBTOXGR == -3 ~ "3", MYBTOXGR == -4 ~ "4", 
          MYBTOXGR == "<MYMissing>" ~ "Missing")))
      anl <- dplyr::mutate(anl, ATOXGR_GP = factor(ATOXGR_GP, levels = c(dplyr::if_else("WGRLOVFL" %in% 
          c("WGRLOVFL", "WGRLOFL"), "Not Low", "Not High"), "1", 
          "2", "3", "4", "Missing")), BTOXGR_GP = factor(BTOXGR_GP, 
          levels = c(dplyr::if_else("WGRLOVFL" %in% c("WGRLOVFL", 
              "WGRLOFL"), "Not Low", "Not High"), "1", "2", "3", 
              "4", "Missing")))
      column_labels <- list(PARAMCD = teal.data::col_labels(anl, 
          fill = FALSE)[["PARAMCD"]], AVISIT = teal.data::col_labels(anl, 
          fill = FALSE)[["AVISIT"]], ATOXGR_GP = dplyr::if_else(TRUE, 
          "Grade at Visit", "Post-baseline Grade"), BTOXGR_GP = "Baseline Grade")
      teal.data::col_labels(anl)[names(column_labels)] <- as.character(column_labels)
      anl
  }

  $layout_prep
  split_fun <- drop_split_levels

  $layout
  lyt <- rtables::basic_table(title = "Grade Summary Table", subtitles = "Worst Flag Variable: WGRLOVFL", 
      show_colcounts = TRUE) %>% rtables::split_cols_by(var = "ARM") %>% 
      rtables::split_rows_by(var = "PARAMCD", split_fun = split_fun, 
          label_pos = "topleft", split_label = teal.data::col_labels(anl, 
              fill = FALSE)[["PARAMCD"]]) %>% rtables::split_rows_by("AVISIT", 
      split_fun = split_fun, label_pos = "topleft", split_label = teal.data::col_labels(anl, 
          fill = FALSE)[["AVISIT"]]) %>% rtables::split_rows_by(var = "ATOXGR_GP", 
      split_fun = split_fun, label_pos = "topleft", split_label = teal.data::col_labels(anl, 
          fill = FALSE)[["ATOXGR_GP"]]) %>% summarize_num_patients(var = "MYUSUBJID", 
      .stats = c("unique_count")) %>% count_occurrences(vars = "BTOXGR_GP", 
      denom = "n", drop = TRUE, .indent_mods = 4L) %>% append_varlabels(anl, 
      "BTOXGR_GP", indent = 3L)

  $table
  {
      table <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = adsl) %>% 
          rtables::prune_table()
  }