| create_dcut | R Documentation | 
After filtering the input DS dataset (based on the given filter condition), any
records where the SDTMv date/time variable is on or before the datacut date/time (after
imputations) will be returned in the output datacut dataset (DCUT). Note that ds_date_var
and cut_date inputs must be in ISO 8601 format (YYYY-MM-DDThh:mm:ss) and will be imputed
using the impute_sdtm() and impute_dcutdtc() functions.
create_dcut(dataset_ds, ds_date_var, filter, cut_date, cut_description)
| dataset_ds | Input DS SDTMv dataset | 
| ds_date_var | Character date/time variable in the DS SDTMv to be compared against the datacut date | 
| filter | Condition to filter patients in DS, should give 1 row per patient | 
| cut_date | Datacut date/time, e.g. "2022-10-22", or NA if no date cut is to be applied | 
| cut_description | Datacut date/time description, e.g. "Clinical Cut Off Date" | 
Datacut dataset containing the variables USUBJID, DCUTDTC, DCUTDTM and
DCUTDESC.
Alana Harris
ds <- tibble::tribble(
  ~USUBJID, ~DSSEQ, ~DSDECOD, ~DSSTDTC,
  "subject1", 1, "INFORMED CONSENT", "2020-06-23",
  "subject1", 2, "RANDOMIZATION", "2020-08-22",
  "subject1", 3, "WITHDRAWAL BY SUBJECT", "2020-05-01",
  "subject2", 1, "INFORMED CONSENT", "2020-07-13",
  "subject3", 1, "INFORMED CONSENT", "2020-06-03",
  "subject4", 1, "INFORMED CONSENT", "2021-01-01",
  "subject4", 2, "RANDOMIZATION", "2023-01-01"
)
dcut <- create_dcut(
  dataset_ds = ds,
  ds_date_var = DSSTDTC,
  filter = DSDECOD == "RANDOMIZATION",
  cut_date = "2022-01-01",
  cut_description = "Clinical Cutoff Date"
)
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