admiral (version 1.1.1)

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

Description

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, ...)

Value

The input dataset with the variables derived by the derivation added

Arguments

dataset

Input dataset

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. The function must provide the dataset argument and all arguments specified in the params() objects passed to the arg argument.

Please note that it is not possible to specify {dplyr} functions like mutate() or summarize().

args

Arguments of the derivation

A params() object is expected.

...

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.

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.

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

See Also

params() restrict_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")
  )
)