Filter a tagged dataset with mandatory exclusion documentation

Works exactly like dplyr::filter() but requires a reason for every exclusion. Rows that do not meet the filter conditions are captured in the session exclusion registry with their USUBJID (if present), lineage ID, and the documented reason.

Usage

lg_filter(data, ..., reason, population = NULL, reason_code = NULL)

Arguments

data: An lg_df from lg_tag().
...: Filter conditions, passed to dplyr::filter().
reason: Character. Mandatory. Why these rows are being excluded. E.g. "Not randomised (RANDFL != 'Y')".
population: Character or NULL. Which population flag this exclusion relates to (e.g. "SAFFL"). Used to group the exclusion listing.
reason_code: Character or NULL. Short controlled-vocabulary code for this exclusion (e.g. "NOT_RANDOMISED"). Useful for programmatic querying of the exclusion registry.

Value

An lg_df containing only the rows that passed the filter. Excluded rows are recorded in the session store.

Details

reason has no default. Undocumented exclusions are a compliance failure : this is enforced at the R level, not by convention.

Examples

lg_start()
#> lineager: session started
adsl <- lg_tag(
  data.frame(USUBJID = c("01", "02", "03"),
             RANDFL  = c("Y", "N", "Y"),
             SAFFL   = c("Y", "N", "Y")),
  dataset_id = "ADSL"
)
#> lineager: tagged 'ADSL' — 3 rows, 3 cols

adsl_rand <- lg_filter(
  adsl,
  RANDFL == "Y",
  reason      = "Not randomised (RANDFL != 'Y')",
  reason_code = "NOT_RANDOMISED",
  population  = "RANDFL"
)
#> lineager: [ADSL] filter 'Not randomised (RANDFL != 'Y')' — 3 in, 2 out, 1 excluded