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Sort Stacked Hierarchical ARDs

Source: R/sort_ard_hierarchical.R
sort_ard_hierarchical.Rd

[Experimental]

This function is used to sort stacked hierarchical ARDs.

For the purposes of this function, we define a "variable group" as a combination of ARD rows grouped by the combination of all their variable levels, but excluding any by variables.

Usage 

sort_ard_hierarchical(x, sort = everything() ~ "descending")

Arguments

x

(card)
a stacked hierarchical ARD of class 'card' created using ard_stack_hierarchical() or ard_stack_hierarchical_count().

sort

(formula-list-selector, string)
a named list, a list of formulas, a single formula where the list element is a named list of functions (or the RHS of a formula), or a single string specifying the types of sorting to perform at each hierarchy variable level. If the sort method for any variable is not specified then the method will default to "descending". If a single unnamed string is supplied it is applied to all variables. For each variable, the value specified must be one of:

  • "alphanumeric" - at the specified hierarchy level of the ARD, groups are ordered alphanumerically (i.e. A to Z) by variable_level text.

  • "descending" - within each variable group of the ARD at the specified hierarchy level, count sums are calculated for each group and groups are sorted in descending order by sum. When sort is "descending" for a given variable and n is included in statistic for the variable then n is used to calculate variable group sums, otherwise p is used. If neither n nor p are present in x for the variable, an error will occur.

Defaults to everything() ~ "descending".

Value

an ARD data frame of class 'card'

Note

If overall data is present in x (i.e. the ARD was created with ard_stack_hierarchical(overall=TRUE)), the overall data will be sorted last within each variable group (i.e. after any other rows with the same combination of variable levels).

See also

filter_ard_hierarchical()

Examples 

ard_stack_hierarchical(
  ADAE,
  variables = c(AESOC, AEDECOD),
  by = TRTA,
  denominator = ADSL,
  id = USUBJID
) |>
  sort_ard_hierarchical(AESOC ~ "alphanumeric")
#> {cards} data frame: 2394 x 13
#>    group1 group1_level group2 group2_level variable variable_level stat_name
#> 1    <NA>                <NA>                  TRTA        Placebo         n
#> 2    <NA>                <NA>                  TRTA        Placebo         N
#> 3    <NA>                <NA>                  TRTA        Placebo         p
#> 4    <NA>                <NA>                  TRTA      Xanomeli…         n
#> 5    <NA>                <NA>                  TRTA      Xanomeli…         N
#> 6    <NA>                <NA>                  TRTA      Xanomeli…         p
#> 7    <NA>                <NA>                  TRTA      Xanomeli…         n
#> 8    <NA>                <NA>                  TRTA      Xanomeli…         N
#> 9    <NA>                <NA>                  TRTA      Xanomeli…         p
#> 10   TRTA      Placebo   <NA>                 AESOC      CARDIAC …         n
#>    stat_label  stat
#> 1           n    86
#> 2           N   254
#> 3           % 0.339
#> 4           n    84
#> 5           N   254
#> 6           % 0.331
#> 7           n    84
#> 8           N   254
#> 9           % 0.331
#> 10          n    13
#> ℹ 2384 more rows
#> ℹ Use `print(n = ...)` to see more rows
#> ℹ 4 more variables: context, fmt_fun, warning, error

ard_stack_hierarchical_count(
  ADAE,
  variables = c(AESOC, AEDECOD),
  by = TRTA,
  denominator = ADSL
) |>
  sort_ard_hierarchical(sort = list(AESOC ~ "alphanumeric", AEDECOD ~ "descending"))
#> {cards} data frame: 804 x 13
#>    group1 group1_level group2 group2_level variable variable_level stat_name
#> 1    <NA>                <NA>                  TRTA        Placebo         n
#> 2    <NA>                <NA>                  TRTA        Placebo         N
#> 3    <NA>                <NA>                  TRTA        Placebo         p
#> 4    <NA>                <NA>                  TRTA      Xanomeli…         n
#> 5    <NA>                <NA>                  TRTA      Xanomeli…         N
#> 6    <NA>                <NA>                  TRTA      Xanomeli…         p
#> 7    <NA>                <NA>                  TRTA      Xanomeli…         n
#> 8    <NA>                <NA>                  TRTA      Xanomeli…         N
#> 9    <NA>                <NA>                  TRTA      Xanomeli…         p
#> 10   TRTA      Placebo   <NA>                 AESOC      CARDIAC …         n
#>    stat_label  stat
#> 1           n    86
#> 2           N   254
#> 3           % 0.339
#> 4           n    84
#> 5           N   254
#> 6           % 0.331
#> 7           n    84
#> 8           N   254
#> 9           % 0.331
#> 10          n    27
#> ℹ 794 more rows
#> ℹ Use `print(n = ...)` to see more rows
#> ℹ 4 more variables: context, fmt_fun, warning, error