cards (version 0.3.0)

ard_hierarchical: Hierarchical ARD Statistics

Description

Performs hierarchical or nested tabulations, e.g. tabulates AE terms nested within AE system organ class.

• ard_hierarchical() includes summaries for the last variable listed in the variables argument, nested within the other variables included.

• ard_hierarchical_count() includes summaries for all variables listed in the variables argument each summary nested within the preceding variables, e.g. variables=c(AESOC, AEDECOD) summarizes AEDECOD nested in AESOC, and also summarizes the counts of AESOC.

Usage

ard_hierarchical(data, ...)
ard_hierarchical_count(data, ...)
# S3 method for data.frame
ard_hierarchical(
  data,
  variables,
  by = dplyr::group_vars(data),
  statistic = everything() ~ c("n", "N", "p"),
  denominator = NULL,
  fmt_fn = NULL,
  stat_label = everything() ~ default_stat_labels(),
  id = NULL,
  ...
)
# S3 method for data.frame
ard_hierarchical_count(
  data,
  variables,
  by = dplyr::group_vars(data),
  fmt_fn = NULL,
  stat_label = everything() ~ default_stat_labels(),
  ...
)

Value

an ARD data frame of class 'card'

Arguments

data

(data.frame)
a data frame

...

Arguments passed to methods.

variables

(tidy-select)
variables to perform the nested/hierarchical tabulations within.

by

(tidy-select)
variables to perform tabulations by. All combinations of the variables specified here appear in results. Default is dplyr::group_vars(data).

statistic

(formula-list-selector)
a named list, a list of formulas, or a single formula where the list element one or more of c("n", "N", "p") (or the RHS of a formula).

denominator

(data.frame, integer)
Specify this optional argument to change the denominator, e.g. the "N" statistic. Default is NULL. See below for details.

fmt_fn

(formula-list-selector)
a named list, a list of formulas, or a single formula where the list element is a named list of functions (or the RHS of a formula), e.g. list(mpg = list(mean = \(x) round(x, digits = 2) |> as.character())).

stat_label

(formula-list-selector)
a named list, a list of formulas, or a single formula where the list element is either a named list or a list of formulas defining the statistic labels, e.g. everything() ~ list(n = "n", p = "pct") or everything() ~ list(n ~ "n", p ~ "pct").

id

(tidy-select)
an optional argument used to assert there are no duplicates within the c(id, variables) columns.

Denominators

By default, the ard_categorical() function returns the statistics "n", "N", and "p", where little "n" are the counts for the variable levels, and big "N" is the number of non-missing observations. The default calculation for the percentage is merely p = n/N.

However, it is sometimes necessary to provide a different "N" to use as the denominator in this calculation. For example, in a calculation of the rates of various observed adverse events, you may need to update the denominator to the number of enrolled subjects.

In such cases, use the denominator argument to specify a new definition of "N", and subsequently "p". The argument expects one of the following inputs:

• a data frame. Any columns in the data frame that overlap with the by/strata columns will be used to calculate the new "N".

• an integer. This single integer will be used as the new "N"

• a string: one of "column", "row", or "cell". "column" is equivalent to denominator=NULL. "row" gives 'row' percentages where by/strata columns are the 'top' of a cross table, and the variables are the rows. "cell" gives percentages where the denominator is the number of non-missing rows in the source data frame.

• a structured data frame. The data frame will include columns from by/strata. The last column must be named "...ard_N...". The integers in this column will be used as the updated "N" in the calculations.

Examples

ard_hierarchical(
  data = ADAE |>
    dplyr::slice_tail(n = 1L, by = c(USUBJID, TRTA, AESOC, AEDECOD)),
  variables = c(AESOC, AEDECOD),
  by = TRTA,
  id = USUBJID,
  denominator = ADSL |> dplyr::rename(TRTA = ARM)
)

ard_hierarchical_count(
  data = ADAE,
  variables = c(AESOC, AEDECOD),
  by = TRTA
)