Skip to contents

Missing ARD Statistics

Source: R/ard_missing.R
ard_missing.Rd

Compute Analysis Results Data (ARD) for statistics related to data missingness.

Usage 

ard_missing(
  data,
  variables,
  by = dplyr::group_vars(data),
  statistic = everything() ~ missing_summary_fns(),
  fmt_fn = NULL,
  stat_label = everything() ~ default_stat_labels()
)

Arguments

data

(data.frame)
a data frame

variables

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

by

(tidy-select)
results are tabulated by all combinations of the columns specified.

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

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

Value

an ARD data frame of class 'card'

Examples 

ard_missing(ADSL, by = "ARM", variables = "AGE")
#> {cards} data frame: 15 x 10
#>    group1 group1_level variable stat_name stat_label stat
#> 1     ARM      Placebo      AGE     N_obs  Vector L…   86
#> 2     ARM      Placebo      AGE    N_miss  N Missing    0
#> 3     ARM      Placebo      AGE N_nonmiss  N Non-mi…   86
#> 4     ARM      Placebo      AGE    p_miss  % Missing    0
#> 5     ARM      Placebo      AGE p_nonmiss  % Non-mi…    1
#> 6     ARM    Xanomeli…      AGE     N_obs  Vector L…   84
#> 7     ARM    Xanomeli…      AGE    N_miss  N Missing    0
#> 8     ARM    Xanomeli…      AGE N_nonmiss  N Non-mi…   84
#> 9     ARM    Xanomeli…      AGE    p_miss  % Missing    0
#> 10    ARM    Xanomeli…      AGE p_nonmiss  % Non-mi…    1
#> 11    ARM    Xanomeli…      AGE     N_obs  Vector L…   84
#> 12    ARM    Xanomeli…      AGE    N_miss  N Missing    0
#> 13    ARM    Xanomeli…      AGE N_nonmiss  N Non-mi…   84
#> 14    ARM    Xanomeli…      AGE    p_miss  % Missing    0
#> 15    ARM    Xanomeli…      AGE p_nonmiss  % Non-mi…    1
#> ℹ 4 more variables: context, fmt_fn, warning, error

ADSL |>
  dplyr::group_by(ARM) |>
  ard_missing(
    variables = "AGE",
    statistic = ~ missing_summary_fns("N_miss")
  )
#> {cards} data frame: 3 x 10
#>   group1 group1_level variable stat_name stat_label stat
#> 1    ARM      Placebo      AGE    N_miss  N Missing    0
#> 2    ARM    Xanomeli…      AGE    N_miss  N Missing    0
#> 3    ARM    Xanomeli…      AGE    N_miss  N Missing    0
#> ℹ 4 more variables: context, fmt_fn, warning, error