score_occurrences {tern}

Occurrence table sorting

Description

Functions to score occurrence table subtables and rows which can be used in the sorting of occurrence tables.

Usage

score_occurrences(table_row)

score_occurrences_cols(...)

score_occurrences_subtable(...)

score_occurrences_cont_cols(...)

Arguments

table_row

(TableRow)
an analysis row in a occurrence table.

...

arguments for row or column access, see rtables_access: either col_names (character) including the names of the columns which should be used, or alternatively col_indices (integer) giving the indices directly instead.

Value

• score_occurrences() returns the sum of counts across all columns of a table row.

• score_occurrences_cols() returns a function that sums counts across all specified columns of a table row.

• score_occurrences_subtable() returns a function that sums counts in each subtable across all specified columns.

• score_occurrences_cont_cols() returns a function that sums counts in the first content row in specified columns.

Functions

• score_occurrences(): Scoring function which sums the counts across all columns. It will fail if anything else but counts are used.

• score_occurrences_cols(): Scoring functions can be produced by this constructor to only include specific columns in the scoring. See h_row_counts() for further information.

• score_occurrences_subtable(): Scoring functions produced by this constructor can be used on subtables: They sum up all specified column counts in the subtable. This is useful when there is no available content row summing up these counts.

• score_occurrences_cont_cols(): Produces a score function for sorting table by summing the first content row in specified columns. Note that this is extending rtables::cont_n_onecol() and rtables::cont_n_allcols().

See Also

h_row_first_values()

h_row_counts()

Examples

lyt <- basic_table() %>%
  split_cols_by("ARM") %>%
  add_colcounts() %>%
  analyze_num_patients(
    vars = "USUBJID",
    .stats = c("unique"),
    .labels = c("Total number of patients with at least one event")
  ) %>%
  split_rows_by("AEBODSYS", child_labels = "visible", nested = FALSE) %>%
  summarize_num_patients(
    var = "USUBJID",
    .stats = c("unique", "nonunique"),
    .labels = c(
      "Total number of patients with at least one event",
      "Total number of events"
    )
  ) %>%
  count_occurrences(vars = "AEDECOD")

tbl <- build_table(lyt, tern_ex_adae, alt_counts_df = tern_ex_adsl) %>%
  prune_table()

tbl_sorted <- tbl %>%
  sort_at_path(path = c("AEBODSYS", "*", "AEDECOD"), scorefun = score_occurrences)

tbl_sorted

score_cols_a_and_b <- score_occurrences_cols(col_names = c("A: Drug X", "B: Placebo"))

# Note that this here just sorts the AEDECOD inside the AEBODSYS. The AEBODSYS are not sorted.
# That would require a second pass of `sort_at_path`.
tbl_sorted <- tbl %>%
  sort_at_path(path = c("AEBODSYS", "*", "AEDECOD"), scorefun = score_cols_a_and_b)

tbl_sorted

score_subtable_all <- score_occurrences_subtable(col_names = names(tbl))

# Note that this code just sorts the AEBODSYS, not the AEDECOD within AEBODSYS. That
# would require a second pass of `sort_at_path`.
tbl_sorted <- tbl %>%
  sort_at_path(path = c("AEBODSYS"), scorefun = score_subtable_all, decreasing = FALSE)

tbl_sorted