derive_var_extreme_dtm: Derive First or Last Datetime from Multiple Sources
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View source: R/derive_var_extreme_date.R

derive_var_extreme_dtm

R Documentation

Derive First or Last Datetime from Multiple Sources

Description

The derive_var_extreme_dtm() function has been superseded in favor of derive_vars_extreme_event().

Add the first or last datetime from multiple sources to the dataset, e.g., the last known alive datetime (LSTALVDTM).

Usage

derive_var_extreme_dtm(
  dataset,
  new_var,
  ...,
  source_datasets,
  mode,
  subject_keys = get_admiral_option("subject_keys")
)

Arguments

`dataset`	Input dataset The variables specified by the `subject_keys` argument are expected to be in the dataset.
`new_var`	Name of variable to create
`...`	Source(s) of dates. One or more `date_source()` objects are expected.
`source_datasets`	A named `list` containing datasets in which to search for the first or last date
`mode`	Selection mode (first or last) If `"first"` is specified, the first date for each subject is selected. If `"last"` is specified, the last date for each subject is selected. Permitted Values: `"first"`, `"last"`
`subject_keys`	Variables to uniquely identify a subject A list of expressions where the expressions are symbols as returned by `exprs()` is expected.

Details

The following steps are performed to create the output dataset:

For each source dataset the observations as specified by the filter element are selected and observations where date is NA are removed. Then for each patient the first or last observation (with respect to date and mode) is selected.
The new variable is set to the variable or expression specified by the date element. If this is a date variable (rather than datetime), then the time is imputed as "00:00:00".
The variables specified by the set_values_to element are added.
The selected observations of all source datasets are combined into a single dataset.
For each patient the first or last observation (with respect to the new variable and mode) from the single dataset is selected and the new variable is merged to the input dataset.

Value

The input dataset with the new variable added.

Examples

library(dplyr, warn.conflicts = FALSE)
library(lubridate)
dm <- tribble(
  ~STUDYID,  ~DOMAIN,  ~USUBJID, ~AGE,   ~AGEU,
  "PILOT01",    "DM", "01-1130",   84, "YEARS",
  "PILOT01",    "DM", "01-1133",   81, "YEARS",
  "PILOT01",    "DM", "01-1211",   76, "YEARS",
  "PILOT01",    "DM", "09-1081",   86, "YEARS",
  "PILOT01",    "DM", "09-1088",   69, "YEARS"
)
ae <- tribble(
  ~STUDYID,  ~DOMAIN,  ~USUBJID, ~AESEQ,     ~AESTDTC,     ~AEENDTC,
  "PILOT01",    "AE", "01-1130",      5, "2014-05-09", "2014-05-09",
  "PILOT01",    "AE", "01-1130",      6, "2014-05-22",           NA,
  "PILOT01",    "AE", "01-1130",      4, "2014-05-09", "2014-05-09",
  "PILOT01",    "AE", "01-1130",      8, "2014-05-22",           NA,
  "PILOT01",    "AE", "01-1130",      7, "2014-05-22",           NA,
  "PILOT01",    "AE", "01-1130",      2, "2014-03-09", "2014-03-09",
  "PILOT01",    "AE", "01-1130",      1, "2014-03-09", "2014-03-16",
  "PILOT01",    "AE", "01-1130",      3, "2014-03-09", "2014-03-16",
  "PILOT01",    "AE", "01-1133",      1, "2012-12-27",           NA,
  "PILOT01",    "AE", "01-1133",      3, "2012-12-27",           NA,
  "PILOT01",    "AE", "01-1133",      2, "2012-12-27",           NA,
  "PILOT01",    "AE", "01-1133",      4, "2012-12-27",           NA,
  "PILOT01",    "AE", "01-1211",      5, "2012-11-29",           NA,
  "PILOT01",    "AE", "01-1211",      1, "2012-11-16",           NA,
  "PILOT01",    "AE", "01-1211",      7, "2013-01-11",           NA,
  "PILOT01",    "AE", "01-1211",      8, "2013-01-11",           NA,
  "PILOT01",    "AE", "01-1211",      4, "2012-11-22",           NA,
  "PILOT01",    "AE", "01-1211",      2, "2012-11-21", "2012-11-21",
  "PILOT01",    "AE", "01-1211",      3, "2012-11-21",           NA,
  "PILOT01",    "AE", "01-1211",      6, "2012-12-09",           NA,
  "PILOT01",    "AE", "01-1211",      9, "2013-01-14", "2013-01-14",
  "PILOT01",    "AE", "09-1081",      2, "2014-05-01",           NA,
  "PILOT01",    "AE", "09-1081",      1, "2014-04-07",           NA,
  "PILOT01",    "AE", "09-1088",      1, "2014-05-08",           NA,
  "PILOT01",    "AE", "09-1088",      2, "2014-08-02",           NA
)
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, "2013-04-29T10:13",
  "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"
)
adsl <- tribble(
  ~STUDYID,   ~USUBJID,              ~TRTEDTM,
  "PILOT01", "01-1130", "2014-08-16 23:59:59",
  "PILOT01", "01-1133", "2013-04-28 23:59:59",
  "PILOT01", "01-1211", "2013-01-12 23:59:59",
  "PILOT01", "09-1081", "2014-04-27 23:59:59",
  "PILOT01", "09-1088", "2014-10-09 23:59:59"
) %>%
  mutate(
    TRTEDTM = as_datetime(TRTEDTM)
  )

# derive last known alive datetime (LSTALVDTM)
ae_start <- date_source(
  dataset_name = "ae",
  date = convert_dtc_to_dtm(AESTDTC, highest_imputation = "M"),
)
ae_end <- date_source(
  dataset_name = "ae",
  date = convert_dtc_to_dtm(AEENDTC, highest_imputation = "M"),
)

ae_ext <- ae %>%
  derive_vars_dtm(
    dtc = AESTDTC,
    new_vars_prefix = "AEST",
    highest_imputation = "M"
  ) %>%
  derive_vars_dtm(
    dtc = AEENDTC,
    new_vars_prefix = "AEEN",
    highest_imputation = "M"
  )

lb_date <- date_source(
  dataset_name = "lb",
  date = convert_dtc_to_dtm(LBDTC),
)

lb_ext <- derive_vars_dtm(
  lb,
  dtc = LBDTC,
  new_vars_prefix = "LB"
)

adsl_date <- date_source(
  dataset_name = "adsl",
  date = TRTEDTM
)

dm %>%
  derive_var_extreme_dtm(
    new_var = LSTALVDTM,
    ae_start, ae_end, lb_date, adsl_date,
    source_datasets = list(
      adsl = adsl,
      ae = ae_ext,
      lb = lb_ext
    ),
    mode = "last"
  ) %>%
  select(USUBJID, LSTALVDTM)

# derive last alive datetime and traceability variables
ae_start <- date_source(
  dataset_name = "ae",
  date = convert_dtc_to_dtm(AESTDTC, highest_imputation = "M"),
  set_values_to = exprs(
    LALVDOM = "AE",
    LALVSEQ = AESEQ,
    LALVVAR = "AESTDTC"
  )
)

ae_end <- date_source(
  dataset_name = "ae",
  date = convert_dtc_to_dtm(AEENDTC, highest_imputation = "M"),
  set_values_to = exprs(
    LALVDOM = "AE",
    LALVSEQ = AESEQ,
    LALVVAR = "AEENDTC"
  )
)
lb_date <- date_source(
  dataset_name = "lb",
  date = convert_dtc_to_dtm(LBDTC),
  set_values_to = exprs(
    LALVDOM = "LB",
    LALVSEQ = LBSEQ,
    LALVVAR = "LBDTC"
  )
)

adsl_date <- date_source(
  dataset_name = "adsl",
  date = TRTEDTM,
  set_values_to = exprs(
    LALVDOM = "ADSL",
    LALVSEQ = NA_integer_,
    LALVVAR = "TRTEDTM"
  )
)

dm %>%
  derive_var_extreme_dtm(
    new_var = LSTALVDTM,
    ae_start, ae_end, lb_date, adsl_date,
    source_datasets = list(
      adsl = adsl,
      ae = ae_ext,
      lb = lb_ext
    ),
    mode = "last"
  ) %>%
  select(USUBJID, LSTALVDTM, LALVDOM, LALVSEQ, LALVVAR)

admiral documentation built on June 22, 2024, 9:06 a.m.