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ARD Selectors

Source: R/selectors.R
selectors.Rd

These selection helpers match variables according to a given pattern.

  • all_ard_groups(): Use this function in dplyr selecting environments, such as dplyr::select(). Function selects grouping columns, e.g. columns named "group##" or "group##_level".

  • all_ard_variables(): Use this function in dplyr selecting environments, such as dplyr::select(). Function selects variables columns, e.g. columns named "variable" or "variable_level".

Usage 

all_ard_groups(types = c("names", "levels"))

all_ard_variables(types = c("names", "levels"))

Arguments

types

(character)
type(s) of columns to select. "names" selects the columns variable name columns, and "levels" selects the level columns. Default is c("names", "levels").

Value

tidyselect output

Examples 

ard <- ard_categorical(ADSL, by = "ARM", variables = "AGEGR1")

ard |> dplyr::select(all_ard_groups())
#> {cards} data frame: 27 x 2
#>    group1 group1_level
#> 1     ARM      Placebo
#> 2     ARM      Placebo
#> 3     ARM      Placebo
#> 4     ARM    Xanomeli…
#> 5     ARM    Xanomeli…
#> 6     ARM    Xanomeli…
#> 7     ARM    Xanomeli…
#> 8     ARM    Xanomeli…
#> 9     ARM    Xanomeli…
#> 10    ARM      Placebo
#> ℹ 17 more rows
#> ℹ Use `print(n = ...)` to see more rows
ard |> dplyr::select(all_ard_variables())
#> {cards} data frame: 27 x 2
#>    variable variable_level
#> 1    AGEGR1          65-80
#> 2    AGEGR1          65-80
#> 3    AGEGR1          65-80
#> 4    AGEGR1          65-80
#> 5    AGEGR1          65-80
#> 6    AGEGR1          65-80
#> 7    AGEGR1          65-80
#> 8    AGEGR1          65-80
#> 9    AGEGR1          65-80
#> 10   AGEGR1            <65
#> ℹ 17 more rows
#> ℹ Use `print(n = ...)` to see more rows