ARD Missing Survey Statistics — ard_missing.survey.design • cardx

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

Usage

# S3 method for survey.design
ard_missing(
  data,
  variables,
  by = NULL,
  statistic = everything() ~ c("N_obs", "N_miss", "N_nonmiss", "p_miss", "p_nonmiss",
    "N_obs_unweighted", "N_miss_unweighted", "N_nonmiss_unweighted", "p_miss_unweighted",
    "p_nonmiss_unweighted"),
  fmt_fn = NULL,
  stat_label = everything() ~ list(N_obs = "Total N", N_miss = "N Missing", N_nonmiss =
    "N not Missing", p_miss = "% Missing", p_nonmiss = "% not Missing",
    N_obs_unweighted = "Total N (unweighted)", N_miss_unweighted =
    "N Missing (unweighted)", N_nonmiss_unweighted = "N not Missing (unweighted)",
    p_miss_unweighted = "% Missing (unweighted)", p_nonmiss_unweighted =
    "% not Missing (unweighted)"),
  ...
)

Arguments

data: (survey.design)
a design object often created with survey::svydesign().
variables: (tidy-select)
columns to include in summaries.
by: (tidy-select)
results are calculated for all combinations of the column specified and the variables. A single column may be specified.
statistic: (formula-list-selector)
a named list, a list of formulas, or a single formula where the list element is a character vector of statistic names to include. See default value for options.
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").
...: These dots are for future extensions and must be empty.

Value

an ARD data frame of class 'card'

Examples

svy_titanic <- survey::svydesign(~1, data = as.data.frame(Titanic), weights = ~Freq)

ard_missing(svy_titanic, variables = c(Class, Age), by = Survived)
#> {cards} data frame: 40 x 10
#>      group1 group1_level variable            stat_name stat_label stat
#> 1  Survived           No    Class            N_nonmiss  N not Mi… 1490
#> 2  Survived           No    Class                N_obs    Total N 1490
#> 3  Survived           No    Class            p_nonmiss  % not Mi…    1
#> 4  Survived           No    Class               N_miss  N Missing    0
#> 5  Survived           No    Class               p_miss  % Missing    0
#> 6  Survived           No    Class    N_miss_unweighted  N Missin…    0
#> 7  Survived           No    Class     N_obs_unweighted  Total N …   16
#> 8  Survived           No    Class    p_miss_unweighted  % Missin…    0
#> 9  Survived           No    Class N_nonmiss_unweighted  N not Mi…   16
#> 10 Survived           No    Class p_nonmiss_unweighted  % not Mi…    1
#> ℹ 30 more rows
#> ℹ Use `print(n = ...)` to see more rows
#> ℹ 4 more variables: context, fmt_fn, warning, error