Compute Analysis Results Data (ARD) for statistics related to data missingness.
Usage
ard_missing(data, ...)
# S3 method for class 'data.frame'
ard_missing(
data,
variables,
by = dplyr::group_vars(data),
statistic = everything() ~ c("N_obs", "N_miss", "N_nonmiss", "p_miss", "p_nonmiss"),
fmt_fun = NULL,
stat_label = everything() ~ default_stat_labels(),
fmt_fn = deprecated(),
...
)Arguments
- data
(
data.frame)
a data frame- ...
Arguments passed to methods.
- variables
(
tidy-select)
columns to include in summaries.- 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_fun
(
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")oreverything() ~ list(mean ~ "Mean", sd ~ "SD").- fmt_fn
Examples
ard_missing(ADSL, by = "ARM", variables = "AGE")
#> # An ARD data frame: 15 × 10
#> group1 group1_level variable context stat_name stat_label stat fmt_fun
#> <chr> <list> <chr> <chr> <chr> <chr> <lis> <list>
#> 1 ARM Placebo AGE missing N_obs Vector Le… 86 0
#> 2 ARM Placebo AGE missing N_miss N Missing 0 0
#> 3 ARM Placebo AGE missing N_nonmiss N Non-mis… 86 0
#> 4 ARM Placebo AGE missing p_miss % Missing 0 <fn>
#> 5 ARM Placebo AGE missing p_nonmiss % Non-mis… 1 <fn>
#> 6 ARM Xanomeline High D… AGE missing N_obs Vector Le… 84 0
#> 7 ARM Xanomeline High D… AGE missing N_miss N Missing 0 0
#> 8 ARM Xanomeline High D… AGE missing N_nonmiss N Non-mis… 84 0
#> 9 ARM Xanomeline High D… AGE missing p_miss % Missing 0 <fn>
#> 10 ARM Xanomeline High D… AGE missing p_nonmiss % Non-mis… 1 <fn>
#> 11 ARM Xanomeline Low Do… AGE missing N_obs Vector Le… 84 0
#> 12 ARM Xanomeline Low Do… AGE missing N_miss N Missing 0 0
#> 13 ARM Xanomeline Low Do… AGE missing N_nonmiss N Non-mis… 84 0
#> 14 ARM Xanomeline Low Do… AGE missing p_miss % Missing 0 <fn>
#> 15 ARM Xanomeline Low Do… AGE missing p_nonmiss % Non-mis… 1 <fn>
#> # ℹ 2 more variables: warning <list>, error <list>
ADSL |>
dplyr::group_by(ARM) |>
ard_missing(
variables = "AGE",
statistic = ~"N_miss"
)
#> # An ARD data frame: 3 × 10
#> group1 group1_level variable context stat_name stat_label stat fmt_fun
#> <chr> <list> <chr> <chr> <chr> <chr> <lis> <list>
#> 1 ARM Placebo AGE missing N_miss N Missing 0 0
#> 2 ARM Xanomeline High Do… AGE missing N_miss N Missing 0 0
#> 3 ARM Xanomeline Low Dose AGE missing N_miss N Missing 0 0
#> # ℹ 2 more variables: warning <list>, error <list>
