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Execute a Derivation with Different Arguments for Subsets of the Input Dataset

Source: R/slice_derivation.R
slice_derivation.Rd

The input dataset is split into slices (subsets) and for each slice the derivation is called separately. Some or all arguments of the derivation may vary depending on the slice.

Usage

slice_derivation(dataset, derivation, args = NULL, ...)

Arguments

dataset

Input dataset

Default value

none

derivation

Derivation

A function that performs a specific derivation is expected. A derivation adds variables or observations to a dataset. The first argument of a derivation must expect a dataset and the derivation must return a dataset. All expected arguments for the derivation function must be provided through the params() object passed to the args argument or be provided in every derivation_slice().

Default value

none

args

Arguments of the derivation

A params() object is expected.

Default value

NULL

...

A derivation_slice() object is expected

Each slice defines a subset of the input dataset and some of the parameters for the derivation. The derivation is called on the subset with the parameters specified by the args parameter and the args field of the derivation_slice() object. If a parameter is specified for both, the value in derivation_slice() overwrites the one in args.

Default value

none

Value

The input dataset with the variables derived by the derivation added

Details

For each slice the derivation is called on the subset defined by the filter field of the derivation_slice() object and with the parameters specified by the args parameter and the args field of the derivation_slice() object. If a parameter is specified for both, the value in derivation_slice() overwrites the one in args.

  • Observations that match with more than one slice are only considered for the first matching slice.

  • The derivation is called for slices with no observations.

  • Observations with no match to any of the slices are included in the output dataset but the derivation is not called for them.

It is also possible to pass functions from outside the {admiral} package to slice_derivation(), e.g. an extension package function, or dplyr::mutate(). The only requirement for a function being passed to derivation is that it must take a dataset as its first argument and return a dataset.

See also

params() restrict_derivation() call_derivation()

Higher Order Functions: call_derivation(), derivation_slice(), restrict_derivation()

Examples

library(tibble)
library(stringr)
advs <- tribble(
  ~USUBJID, ~VSDTC,       ~VSTPT,
  "1",      "2020-04-16", NA_character_,
  "1",      "2020-04-16", "BEFORE TREATMENT"
)

# For the second slice filter is set to TRUE. Thus derive_vars_dtm is called
# with time_imputation = "last" for all observations which do not match for the
# first slice.
slice_derivation(
  advs,
  derivation = derive_vars_dtm,
  args = params(
    dtc = VSDTC,
    new_vars_prefix = "A"
  ),
  derivation_slice(
    filter = str_detect(VSTPT, "PRE|BEFORE"),
    args = params(time_imputation = "first")
  ),
  derivation_slice(
    filter = TRUE,
    args = params(time_imputation = "last")
  )
)
#> # A tibble: 2 × 5
#>   USUBJID VSDTC      VSTPT            ADTM                ATMF 
#>   <chr>   <chr>      <chr>            <dttm>              <chr>
#> 1 1       2020-04-16 BEFORE TREATMENT 2020-04-16 00:00:00 H    
#> 2 1       2020-04-16 NA               2020-04-16 23:59:59 H