score_occurrences: Occurrence table sorting

In tern: Create Common TLGs Used in Clinical Trials

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

tern documentation built on Sept. 24, 2024, 9:06 a.m.