derive_vars_extreme_event: Add the Worst or Best Observation for Each By Group as New...

In Roche-GSK/admiral: ADaM in R Asset Library

Add the Worst or Best Observation for Each By Group as New Variables

Description

Add the first available record from events for each by group as new variables, all variables of the selected observation are kept. It can be used for selecting the extreme observation from a series of user-defined events.

Usage

derive_vars_extreme_event(
  dataset,
  by_vars,
  events,
  tmp_event_nr_var = NULL,
  order,
  mode,
  source_datasets = NULL,
  check_type = "warning",
  new_vars
)

Arguments

dataset	Input dataset The variables specified by the by_vars and order arguments are expected to be in the dataset. Default value none
by_vars	Grouping variables Default value NULL
events	Conditions and new values defining events A list of event() or event_joined() objects is expected. Only observations listed in the events are considered for deriving extreme event. If multiple records meet the filter condition, take the first record sorted by order. The data is grouped by by_vars, i.e., summary functions like all() or any() can be used in condition. For event_joined() events the observations are selected by calling filter_joined(). The condition field is passed to the filter_join argument. Default value none
tmp_event_nr_var	Temporary event number variable The specified variable is added to all source datasets and is set to the number of the event before selecting the records of the event. It can be used in order to determine which record should be used if records from more than one event are selected. The variable is not included in the output dataset. Default value NULL
order	Sort order If a particular event from events has more than one observation, within the event and by group, the records are ordered by the specified order. For handling of NAs in sorting variables see Sort Order. Permitted values list of expressions created by exprs(), e.g., exprs(ADT, desc(AVAL)) Default value none
mode	Selection mode (first or last) If a particular event from events has more than one observation, "first"/"last" is used to select the first/last record of this type of event sorting by order. Permitted values "first", "last" Default value none
source_datasets	Source datasets A named list of datasets is expected. The dataset_name field of event() and event_joined() refers to the dataset provided in the list. Default value NULL
check_type	Check uniqueness? If "warning" or "error" is specified, the specified message is issued if the observations of the input dataset are not unique with respect to the by variables and the order. Permitted values "none", "message", "warning", "error" Default value "warning"
new_vars	Variables to add The specified variables from the events are added to the output dataset. Variables can be renamed by naming the element, i.e., ⁠new_vars = exprs(<new name> = <old name>)⁠. Default value none

Details

1. For each event select the observations to consider:

   1. If the event is of class event, the observations of the source dataset are restricted by condition and then the first or last (mode) observation per by group (by_vars) is selected.

      If the event is of class event_joined, filter_joined() is called to select the observations.

   2. The variables specified by the set_values_to field of the event are added to the selected observations.

   3. The variable specified for tmp_event_nr_var is added and set to the number of the event.

2. All selected observations are bound together.

3. For each group (with respect to the variables specified for the by_vars parameter) the first or last observation (with respect to the order specified for the order parameter and the mode specified for the mode parameter) is selected.

4. The variables specified by the new_vars parameter are added to the selected observations.

5. The variables are added to input dataset.

Value

The input dataset with the best or worst observation of each by group added as new variables.

See Also

event(), event_joined(), derive_extreme_event()

ADSL Functions that returns variable appended to dataset: derive_var_age_years(), derive_vars_aage(), derive_vars_period()

Examples

library(tibble)
library(dplyr)
library(lubridate)

adsl <- tribble(
  ~STUDYID, ~USUBJID, ~TRTEDT, ~DTHDT,
  "PILOT01", "01-1130", ymd("2014-08-16"), ymd("2014-09-13"),
  "PILOT01", "01-1133", ymd("2013-04-28"), ymd(""),
  "PILOT01", "01-1211", ymd("2013-01-12"), ymd(""),
  "PILOT01", "09-1081", ymd("2014-04-27"), ymd(""),
  "PILOT01", "09-1088", ymd("2014-10-09"), ymd("2014-11-01"),
)

lb <- tribble(
  ~STUDYID,  ~DOMAIN,  ~USUBJID, ~LBSEQ,             ~LBDTC,
  "PILOT01",    "LB", "01-1130",    219, "2014-06-07T13:20",
  "PILOT01",    "LB", "01-1130",    322, "2014-08-16T13:10",
  "PILOT01",    "LB", "01-1133",    268, "2013-04-18T15:30",
  "PILOT01",    "LB", "01-1133",    304, "2013-05-01T10:13",
  "PILOT01",    "LB", "01-1211",      8, "2012-10-30T14:26",
  "PILOT01",    "LB", "01-1211",    162, "2013-01-08T12:13",
  "PILOT01",    "LB", "09-1081",     47, "2014-02-01T10:55",
  "PILOT01",    "LB", "09-1081",    219, "2014-05-10T11:15",
  "PILOT01",    "LB", "09-1088",    283, "2014-09-27T12:13",
  "PILOT01",    "LB", "09-1088",    322, "2014-10-09T13:25"
) %>%
  mutate(
    ADT = convert_dtc_to_dt(LBDTC)
  )

derive_vars_extreme_event(
  adsl,
  by_vars = exprs(STUDYID, USUBJID),
  events = list(
    event(
      dataset_name = "adsl",
      condition = !is.na(DTHDT),
      set_values_to = exprs(LSTALVDT = DTHDT, DTHFL = "Y")
    ),
    event(
      dataset_name = "lb",
      condition = !is.na(ADT),
      order = exprs(ADT),
      mode = "last",
      set_values_to = exprs(LSTALVDT = ADT, DTHFL = "N")
    ),
    event(
      dataset_name = "adsl",
      condition = !is.na(TRTEDT),
      order = exprs(TRTEDT),
      mode = "last",
      set_values_to = exprs(LSTALVDT = TRTEDT, DTHFL = "N")
    )
  ),
  source_datasets = list(adsl = adsl, lb = lb),
  tmp_event_nr_var = event_nr,
  order = exprs(LSTALVDT, event_nr),
  mode = "last",
  new_vars = exprs(LSTALVDT, DTHFL)
)

# Derive DTHCAUS from AE and DS domain data
adsl <- tribble(
  ~STUDYID,  ~USUBJID,
  "STUDY01", "PAT01",
  "STUDY01", "PAT02",
  "STUDY01", "PAT03"
)
ae <- tribble(
  ~STUDYID, ~USUBJID, ~AESEQ, ~AEDECOD, ~AEOUT, ~AEDTHDTC,
  "STUDY01", "PAT01", 12, "SUDDEN DEATH", "FATAL", "2021-04-04",
  "STUDY01", "PAT01", 13, "CARDIAC ARREST", "FATAL", "2021-04-03",
)

ds <- tribble(
  ~STUDYID, ~USUBJID, ~DSSEQ, ~DSDECOD, ~DSTERM, ~DSSTDTC,
  "STUDY01", "PAT02", 1, "INFORMED CONSENT OBTAINED", "INFORMED CONSENT OBTAINED", "2021-04-03",
  "STUDY01", "PAT02", 2, "RANDOMIZATION", "RANDOMIZATION", "2021-04-11",
  "STUDY01", "PAT02", 3, "DEATH", "DEATH DUE TO PROGRESSION OF DISEASE", "2022-02-01",
  "STUDY01", "PAT03", 1, "DEATH", "POST STUDY REPORTING OF DEATH", "2022-03-03"
)

derive_vars_extreme_event(
  adsl,
  by_vars = exprs(STUDYID, USUBJID),
  events = list(
    event(
      dataset_name = "ae",
      condition = AEOUT == "FATAL",
      set_values_to = exprs(DTHCAUS = AEDECOD, DTHDT = convert_dtc_to_dt(AEDTHDTC)),
      order = exprs(DTHDT)
    ),
    event(
      dataset_name = "ds",
      condition = DSDECOD == "DEATH" & grepl("DEATH DUE TO", DSTERM),
      set_values_to = exprs(DTHCAUS = DSTERM, DTHDT = convert_dtc_to_dt(DSSTDTC)),
      order = exprs(DTHDT)
    )
  ),
  source_datasets = list(ae = ae, ds = ds),
  tmp_event_nr_var = event_nr,
  order = exprs(DTHDT, event_nr),
  mode = "first",
  new_vars = exprs(DTHCAUS, DTHDT)
)

Roche-GSK/admiral documentation built on April 14, 2025, 12:36 p.m.