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

template_smq generates correct expressions with default arguments

Code
  res
Output
  $data
  {
      anl <- adae
      adsl <- adsl %>% dplyr::mutate(ARMCD = droplevels(ARMCD))
      arm_levels <- levels(adsl[["ARMCD"]])
      anl <- anl %>% dplyr::mutate(ARMCD = factor(ARMCD, levels = arm_levels))
      adsl <- adsl %>% dplyr::mutate(SEX = droplevels(SEX))
      arm_levels <- levels(adsl[["SEX"]])
      anl <- anl %>% dplyr::mutate(SEX = factor(SEX, levels = arm_levels))
      anl <- h_stack_by_baskets(df = anl, baskets = c("SMQ01NAM", 
          "SMQ02NAM", "CQ01NAM"), smq_varlabel = "Standardized MedDRA Query", 
          keys = unique(c("STUDYID", "USUBJID", c("ARMCD", "SEX"), 
              "AEDECOD")))
      if (nrow(anl) == 0) {
          stop("Analysis dataset contains only missing values")
      }
      anl <- df_explicit_na(anl, na_level = "<Missing>")
      adsl <- df_explicit_na(adsl, na_level = "<Missing>")
  }

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE) %>% rtables::split_cols_by(var = "ARMCD") %>% 
      rtables::split_cols_by(var = "SEX") %>% summarize_num_patients(var = "USUBJID", 
      .stats = c("unique"), .labels = c(unique = "Total number of patients with at least one adverse event")) %>% 
      rtables::split_rows_by("SMQ", child_labels = "visible", nested = FALSE, 
          split_fun = trim_levels_in_group("AEDECOD", drop_outlevs = FALSE), 
          indent_mod = -1L, label_pos = "topleft", split_label = teal.data::col_labels(anl, 
              fill = FALSE)[["SMQ"]]) %>% summarize_num_patients(var = "USUBJID", 
      .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one adverse event", 
          nonunique = "Total number of events")) %>% count_occurrences(vars = "AEDECOD", 
      drop = FALSE) %>% append_varlabels(anl, "AEDECOD", indent = 1L)

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

  $sort
  {
      sorted_result <- result %>% sort_at_path(path = c("SMQ"), 
          scorefun = cont_n_allcols) %>% sort_at_path(path = c("SMQ", 
          "*", "AEDECOD"), scorefun = score_occurrences, na.pos = "last")
  }

  $sort_and_prune
  {
      all_zero <- function(tr) {
          !inherits(tr, "ContentRow") && rtables::all_zero_or_na(tr)
      }
      table <- sorted_result %>% rtables::trim_rows(criteria = all_zero)
  }

template_smq generates correct expressions with custom arguments

Code
  res
Output
  $data
  {
      anl <- myadae
      myadsl <- myadsl %>% dplyr::mutate(myARMCD = droplevels(myARMCD))
      arm_levels <- levels(myadsl[["myARMCD"]])
      anl <- anl %>% dplyr::mutate(myARMCD = factor(myARMCD, levels = arm_levels))
      anl <- h_stack_by_baskets(df = anl, baskets = "mybaskets", 
          smq_varlabel = "mylabel", keys = unique(c("STUDYID", 
              "myUSUBJID", "myARMCD", "myAEDECOD")))
      if (nrow(anl) == 0) {
          stop("Analysis dataset contains only missing values")
      }
      anl <- df_explicit_na(anl, na_level = "<Missing>")
      myadsl <- df_explicit_na(myadsl, na_level = "<Missing>")
  }

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE) %>% rtables::split_cols_by(var = "myARMCD") %>% 
      summarize_num_patients(var = "myUSUBJID", .stats = c("unique"), 
          .labels = c(unique = "Total number of patients with at least one adverse event")) %>% 
      rtables::split_rows_by("SMQ", child_labels = "visible", nested = FALSE, 
          split_fun = trim_levels_in_group("myAEDECOD", drop_outlevs = FALSE), 
          indent_mod = -1L, label_pos = "topleft", split_label = teal.data::col_labels(anl, 
              fill = FALSE)[["SMQ"]]) %>% summarize_num_patients(var = "myUSUBJID", 
      .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one adverse event", 
          nonunique = "Total number of events")) %>% count_occurrences(vars = "myAEDECOD", 
      drop = FALSE) %>% append_varlabels(anl, "myAEDECOD", indent = 1L)

  $table
  {
      result <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = myadsl)
  }

  $sort
  {
      sorted_result <- result %>% sort_at_path(path = c("SMQ"), 
          scorefun = cont_n_allcols) %>% sort_at_path(path = c("SMQ", 
          "*", "myAEDECOD"), scorefun = score_occurrences, na.pos = "last")
  }

  $sort_and_prune
  {
      all_zero <- function(tr) {
          !inherits(tr, "ContentRow") && rtables::all_zero_or_na(tr)
      }
      table <- sorted_result %>% rtables::trim_rows(criteria = all_zero)
  }