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

template_abnormality generates correct expressions with default arguments

Code
  res
Output
  $data
  {
      anl <- adlb %>% dplyr::filter(ONTRTFL == "Y" & !is.na(ANRIND) & 
          ANRIND != "<Missing>")
      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>")
  }

  $layout_prep
  {
      map <- h_map_for_count_abnormal(df = anl, variables = list(anl = "ANRIND", 
          split_rows = c("AVISIT", "PARAM")), abnormal = list(low = c("LOW", 
          "LOW LOW"), high = c("HIGH", "HIGH HIGH")), method = "default", 
          na_str = "<Missing>")
  }

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE, title = "my_title", 
      main_footer = "Variables without observed abnormalities are excluded.") %>% 
      rtables::split_cols_by(var = "ARM") %>% rtables::split_rows_by("AVISIT", 
      split_label = teal.data::col_labels(adlb, fill = FALSE)[["AVISIT"]], 
      label_pos = "topleft", split_fun = trim_levels_to_map(map = map)) %>% 
      rtables::split_rows_by("PARAM", split_label = teal.data::col_labels(adlb, 
          fill = FALSE)[["PARAM"]], label_pos = "topleft", split_fun = trim_levels_to_map(map = map)) %>% 
      count_abnormal(var = "ANRIND", abnormal = list(low = c("LOW", 
          "LOW LOW"), high = c("HIGH", "HIGH HIGH")), variables = list(id = "USUBJID", 
          baseline = "BNRIND"), .indent_mods = 4L, exclude_base_abn = FALSE) %>% 
      append_varlabels(adlb, "ANRIND", indent = 2L)

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

template_abnormality generates correct expressions with custom arguments

Code
  res
Output
  $data
  {
      anl <- adlb %>% dplyr::filter(MYTRTFL == "YES" & !is.na(MYANRIND) & 
          MYANRIND != "<Missing>")
      adsl <- adsl %>% dplyr::mutate(ARM = droplevels(ARM))
      arm_levels <- levels(adsl[["ARM"]])
      anl <- anl %>% dplyr::mutate(ARM = factor(ARM, levels = arm_levels))
      anl <- df_explicit_na(anl, na_level = "<Missing>")
      adsl <- df_explicit_na(adsl, na_level = "<Missing>")
  }

  $layout_prep
  {
      map <- h_map_for_count_abnormal(df = anl, variables = list(anl = "MYANRIND", 
          split_rows = c("AVISIT", "PARAMCD")), abnormal = list(Low = "LOW", 
          Medium = "MEDIUM"), method = "default", na_str = "<Missing>")
  }

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE, title = "my_title", 
      main_footer = "Variables without observed abnormalities are excluded.") %>% 
      rtables::split_cols_by(var = "ARM", split_fun = add_overall_level("All Patients", 
          first = FALSE)) %>% rtables::split_rows_by("AVISIT", 
      split_label = teal.data::col_labels(adlb, fill = FALSE)[["AVISIT"]], 
      label_pos = "topleft", split_fun = trim_levels_to_map(map = map)) %>% 
      rtables::split_rows_by("PARAMCD", split_label = teal.data::col_labels(adlb, 
          fill = FALSE)[["PARAMCD"]], label_pos = "topleft", split_fun = trim_levels_to_map(map = map)) %>% 
      count_abnormal(var = "MYANRIND", abnormal = list(Low = "LOW", 
          Medium = "MEDIUM"), variables = list(id = "USUBJID", 
          baseline = "MYBASELINE"), .indent_mods = 4L, exclude_base_abn = TRUE) %>% 
      append_varlabels(adlb, "MYANRIND", indent = 2L)

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

template_abnormality generates correct expressions with customized na_level

Code
  res
Output
  $data
  {
      anl <- adlb %>% dplyr::filter(ONTRTFL == "Y" & !is.na(ANRIND) & 
          ANRIND != "NA")
      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 = "NA")
      adsl <- df_explicit_na(adsl, na_level = "NA")
  }

  $layout_prep
  {
      map <- h_map_for_count_abnormal(df = anl, variables = list(anl = "ANRIND", 
          split_rows = c("AVISIT", "PARAM")), abnormal = list(low = c("LOW", 
          "LOW LOW"), high = c("HIGH", "HIGH HIGH")), method = "default", 
          na_str = "NA")
  }

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE, title = "my_title", 
      main_footer = "Variables without observed abnormalities are excluded.") %>% 
      rtables::split_cols_by(var = "ARM") %>% rtables::split_rows_by("AVISIT", 
      split_label = teal.data::col_labels(adlb, fill = FALSE)[["AVISIT"]], 
      label_pos = "topleft", split_fun = trim_levels_to_map(map = map)) %>% 
      rtables::split_rows_by("PARAM", split_label = teal.data::col_labels(adlb, 
          fill = FALSE)[["PARAM"]], label_pos = "topleft", split_fun = trim_levels_to_map(map = map)) %>% 
      count_abnormal(var = "ANRIND", abnormal = list(low = c("LOW", 
          "LOW LOW"), high = c("HIGH", "HIGH HIGH")), variables = list(id = "USUBJID", 
          baseline = "BNRIND"), .indent_mods = 4L, exclude_base_abn = FALSE) %>% 
      append_varlabels(adlb, "ANRIND", indent = 2L)

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