Continuous ARD Statistics — ard

Compute Analysis Results Data (ARD) for simple continuous summary statistics.

Usage

ard_continuous(data, ...)

# S3 method for class 'data.frame'
ard_continuous(
  data,
  variables,
  by = dplyr::group_vars(data),
  strata = NULL,
  statistic = everything() ~ continuous_summary_fns(),
  fmt_fn = NULL,
  stat_label = everything() ~ default_stat_labels(),
  ...
)

Arguments

data

(data.frame)
a data frame

...

Arguments passed to methods.

variables

(tidy-select)
columns to include in summaries. Default is everything().

by, strata

(tidy-select)
columns to tabulate by/stratify by for summary statistic calculation. Arguments are similar, but with an important distinction:

by: results are calculated for all combinations of the columns specified, including unobserved combinations and unobserved factor levels.

strata: results are calculated for all observed combinations of the columns specified.

Arguments may be used in conjunction with one another.

statistic

(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) mean(x))).

The value assigned to each variable must also be a named list, where the names are used to reference a function and the element is the function object. Typically, this function will return a scalar statistic, but a function that returns a named list of results is also acceptable, e.g. list(conf.low = -1, conf.high = 1). However, when errors occur, the messaging will be less clear in this setting.

fmt_fn

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(mean = "Mean", sd = "SD") or everything() ~ list(mean ~ "Mean", sd ~ "SD").

Value

an ARD data frame of class 'card'

Examples

ard_continuous(ADSL, by = "ARM", variables = "AGE")
#> {cards} data frame: 24 x 10
#>    group1 group1_level variable stat_name stat_label   stat
#> 1     ARM      Placebo      AGE         N          N     86
#> 2     ARM      Placebo      AGE      mean       Mean 75.209
#> 3     ARM      Placebo      AGE        sd         SD   8.59
#> 4     ARM      Placebo      AGE    median     Median     76
#> 5     ARM      Placebo      AGE       p25         Q1     69
#> 6     ARM      Placebo      AGE       p75         Q3     82
#> 7     ARM      Placebo      AGE       min        Min     52
#> 8     ARM      Placebo      AGE       max        Max     89
#> 9     ARM    Xanomeli…      AGE         N          N     84
#> 10    ARM    Xanomeli…      AGE      mean       Mean 74.381
#> ℹ 14 more rows
#> ℹ Use `print(n = ...)` to see more rows
#> ℹ 4 more variables: context, fmt_fn, warning, error

# if a single function returns a named list, the named
# results will be placed in the resulting ARD
ADSL |>
  dplyr::group_by(ARM) |>
  ard_continuous(
    variables = "AGE",
    statistic =
      ~ list(conf.int = \(x) t.test(x)[["conf.int"]] |>
        as.list() |>
        setNames(c("conf.low", "conf.high")))
  )
#> {cards} data frame: 6 x 10
#>   group1 group1_level variable stat_name stat_label   stat
#> 1    ARM      Placebo      AGE  conf.low   conf.low 73.368
#> 2    ARM      Placebo      AGE conf.high  conf.high 77.051
#> 3    ARM    Xanomeli…      AGE  conf.low   conf.low  72.67
#> 4    ARM    Xanomeli…      AGE conf.high  conf.high 76.092
#> 5    ARM    Xanomeli…      AGE  conf.low   conf.low 73.868
#> 6    ARM    Xanomeli…      AGE conf.high  conf.high 77.465
#> ℹ 4 more variables: context, fmt_fn, warning, error