tests/testthat/_snaps/tm_t_mult_events.md

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

template_mult_events generates correct expressions with 1 HLT parameter

Code
  res
Output
  $data
  {
      anl <- adcm
      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 <- anl %>% df_explicit_na(omit_columns = setdiff(names(anl), 
          c("ATC1", "CMDECOD")))
      anl <- anl %>% dplyr::mutate(ASEQ = as.factor(ASEQ))
      adsl <- df_explicit_na(adsl, na_level = "<Missing>")
  }

  $layout_prep
  split_fun <- drop_split_levels

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE) %>% rtables::split_cols_by(var = "ARM") %>% 
      rtables::add_overall_col(label = "All Patients") %>% summarize_num_patients(var = "USUBJID", 
      count_by = "ASEQ", .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
          nonunique = "Total number of treatments")) %>% rtables::split_rows_by("ATC1", 
      child_labels = "visible", nested = FALSE, indent_mod = -1L, 
      split_fun = split_fun, label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC1"])) %>% 
      summarize_num_patients(var = "USUBJID", count_by = "ASEQ", 
          .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
              nonunique = "Total number of treatments")) %>% count_occurrences(vars = "CMDECOD", 
      .indent_mods = -1L) %>% append_varlabels(adcm, "CMDECOD", 
      indent = 1L)

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

  $table_sorted
  {
      sorted_result <- result %>% sort_at_path(path = c("ATC1", 
          "*", "CMDECOD"), scorefun = score_occurrences)
  }

  $final_table
  {
      table <- sorted_result
  }

template_mult_events generates correct expressions with 2 HLT parameters and drop_arm_levels = FALSE

Code
  res
Output
  $data
  {
      anl <- adcm
      adsl <- adsl %>% dplyr::mutate(ARM = droplevels(ARM))
      arm_levels <- levels(adsl[["ARM"]])
      anl <- anl %>% dplyr::mutate(ARM = factor(ARM, levels = arm_levels))
      anl <- anl %>% df_explicit_na(omit_columns = setdiff(names(anl), 
          c("ATC1", "ATC2", "CMDECOD")))
      anl <- anl %>% dplyr::mutate(ASEQ = as.factor(ASEQ))
      adsl <- df_explicit_na(adsl, na_level = "<Missing>")
  }

  $layout_prep
  split_fun <- drop_split_levels

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE) %>% rtables::split_cols_by(var = "ARM") %>% 
      rtables::add_overall_col(label = "All Patients") %>% summarize_num_patients(var = "USUBJID", 
      count_by = "ASEQ", .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
          nonunique = "Total number of treatments")) %>% rtables::split_rows_by("ATC1", 
      child_labels = "visible", nested = FALSE, indent_mod = -1L, 
      split_fun = split_fun, label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC1"])) %>% 
      rtables::split_rows_by("ATC2", child_labels = "visible", 
          nested = TRUE, indent_mod = 0L, split_fun = split_fun, 
          label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC2"])) %>% 
      summarize_num_patients(var = "USUBJID", count_by = "ASEQ", 
          .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
              nonunique = "Total number of treatments")) %>% count_occurrences(vars = "CMDECOD", 
      .indent_mods = -1L) %>% append_varlabels(adcm, "CMDECOD", 
      indent = 2L)

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

  $table_sorted
  {
      sorted_result <- result %>% sort_at_path(path = c("ATC1", 
          "*", "ATC2", "*", "CMDECOD"), scorefun = score_occurrences)
  }

  $final_table
  {
      table <- sorted_result
  }

template_mult_events generates correct expressions with 3 HLT parameters

Code
  res
Output
  $data
  {
      anl <- adcm
      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 <- anl %>% df_explicit_na(omit_columns = setdiff(names(anl), 
          c("ATC1", "ATC2", "ATC3", "CMDECOD")))
      anl <- anl %>% dplyr::mutate(ASEQ = as.factor(ASEQ))
      adsl <- df_explicit_na(adsl, na_level = "<Missing>")
  }

  $layout_prep
  split_fun <- drop_split_levels

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE) %>% rtables::split_cols_by(var = "ARM") %>% 
      rtables::add_overall_col(label = "All Patients") %>% summarize_num_patients(var = "USUBJID", 
      count_by = "ASEQ", .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
          nonunique = "Total number of treatments")) %>% rtables::split_rows_by("ATC1", 
      child_labels = "visible", nested = FALSE, indent_mod = -1L, 
      split_fun = split_fun, label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC1"])) %>% 
      rtables::split_rows_by("ATC2", child_labels = "visible", 
          nested = TRUE, indent_mod = 0L, split_fun = split_fun, 
          label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC2"])) %>% 
      rtables::split_rows_by("ATC3", child_labels = "visible", 
          nested = TRUE, indent_mod = 0L, split_fun = split_fun, 
          label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC3"])) %>% 
      summarize_num_patients(var = "USUBJID", count_by = "ASEQ", 
          .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
              nonunique = "Total number of treatments")) %>% count_occurrences(vars = "CMDECOD", 
      .indent_mods = -1L) %>% append_varlabels(adcm, "CMDECOD", 
      indent = 3L)

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

  $table_sorted
  {
      sorted_result <- result %>% sort_at_path(path = c("ATC1", 
          "*", "ATC2", "*", "ATC3", "*", "CMDECOD"), scorefun = score_occurrences)
  }

  $final_table
  {
      table <- sorted_result
  }

template_mult_events generates correct expressions with 4 HLT parameters

Code
  res
Output
  $data
  {
      anl <- adcm
      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 <- anl %>% df_explicit_na(omit_columns = setdiff(names(anl), 
          c("ATC1", "ATC2", "ATC3", "ATC4", "CMDECOD")))
      anl <- anl %>% dplyr::mutate(ASEQ = as.factor(ASEQ))
      adsl <- df_explicit_na(adsl, na_level = "<Missing>")
  }

  $layout_prep
  split_fun <- drop_split_levels

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE) %>% rtables::split_cols_by(var = "ARM") %>% 
      rtables::add_overall_col(label = "All Patients") %>% summarize_num_patients(var = "USUBJID", 
      count_by = "ASEQ", .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
          nonunique = "Total number of treatments")) %>% rtables::split_rows_by("ATC1", 
      child_labels = "visible", nested = FALSE, indent_mod = -1L, 
      split_fun = split_fun, label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC1"])) %>% 
      rtables::split_rows_by("ATC2", child_labels = "visible", 
          nested = TRUE, indent_mod = 0L, split_fun = split_fun, 
          label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC2"])) %>% 
      rtables::split_rows_by("ATC3", child_labels = "visible", 
          nested = TRUE, indent_mod = 0L, split_fun = split_fun, 
          label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC3"])) %>% 
      rtables::split_rows_by("ATC4", child_labels = "visible", 
          nested = TRUE, indent_mod = 0L, split_fun = split_fun, 
          label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC4"])) %>% 
      summarize_num_patients(var = "USUBJID", count_by = "ASEQ", 
          .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
              nonunique = "Total number of treatments")) %>% count_occurrences(vars = "CMDECOD", 
      .indent_mods = -1L) %>% append_varlabels(adcm, "CMDECOD", 
      indent = 4L)

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

  $table_sorted
  {
      sorted_result <- result %>% sort_at_path(path = c("ATC1", 
          "*", "ATC2", "*", "ATC3", "*", "ATC4", "*", "CMDECOD"), 
          scorefun = score_occurrences)
  }

  $final_table
  {
      table <- sorted_result
  }

template_mult_events generates correct expressions with no HLT parameters

Code
  res
Output
  $data
  {
      anl <- adcm
      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 <- anl %>% df_explicit_na(omit_columns = setdiff(names(anl), 
          "CMDECOD"))
      anl <- anl %>% dplyr::mutate(ASEQ = as.factor(ASEQ))
      adsl <- df_explicit_na(adsl, na_level = "<Missing>")
  }

  $layout_prep
  split_fun <- drop_split_levels

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE) %>% rtables::split_cols_by(var = "ARM") %>% 
      rtables::add_overall_col(label = "All Patients") %>% summarize_num_patients(var = "USUBJID", 
      count_by = "ASEQ", .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
          nonunique = "Total number of treatments")) %>% count_occurrences(vars = "CMDECOD", 
      .indent_mods = -1L) %>% append_varlabels(adcm, "CMDECOD", 
      indent = 0L)

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

  $table_sorted
  {
      sorted_result <- result %>% sort_at_path(path = "CMDECOD", 
          scorefun = score_occurrences)
  }

  $final_table
  {
      table <- sorted_result
  }

template_mult_events generates correct expressions with 1 HLT parameter and without 'All Patients' column

Code
  res
Output
  $data
  {
      anl <- adcm
      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 <- anl %>% df_explicit_na(omit_columns = setdiff(names(anl), 
          c("ATC1", "CMDECOD")))
      anl <- anl %>% dplyr::mutate(ASEQ = as.factor(ASEQ))
      adsl <- df_explicit_na(adsl, na_level = "<Missing>")
  }

  $layout_prep
  split_fun <- drop_split_levels

  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE) %>% rtables::split_cols_by(var = "ARM") %>% 
      summarize_num_patients(var = "USUBJID", count_by = "ASEQ", 
          .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
              nonunique = "Total number of treatments")) %>% rtables::split_rows_by("ATC1", 
      child_labels = "visible", nested = FALSE, indent_mod = -1L, 
      split_fun = split_fun, label_pos = "topleft", split_label = teal.data::col_labels(adcm["ATC1"])) %>% 
      summarize_num_patients(var = "USUBJID", count_by = "ASEQ", 
          .stats = c("unique", "nonunique"), .labels = c(unique = "Total number of patients with at least one treatment", 
              nonunique = "Total number of treatments")) %>% count_occurrences(vars = "CMDECOD", 
      .indent_mods = -1L) %>% append_varlabels(adcm, "CMDECOD", 
      indent = 1L)

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

  $table_sorted
  {
      sorted_result <- result %>% sort_at_path(path = c("ATC1", 
          "*", "CMDECOD"), scorefun = score_occurrences)
  }

  $final_table
  {
      table <- sorted_result
  }

teal.modules.clinical documentation built on April 4, 2025, 12:35 a.m.