sdtm.oak (version 0.1.0)

assign_datetime: Derive an ISO8601 date-time variable

Description

assign_datetime() maps one or more variables with date/time components in a raw dataset to a target SDTM variable following the ISO8601 format.

Usage

assign_datetime(
  tgt_dat = NULL,
  tgt_var,
  raw_dat,
  raw_var,
  raw_fmt,
  raw_unk = c("UN", "UNK"),
  id_vars = oak_id_vars(),
  .warn = TRUE
)

Value

The returned data set depends on the value of tgt_dat:

• If no target dataset is supplied, meaning that tgt_dat defaults to NULL, then the returned data set is raw_dat, selected for the variables indicated in id_vars, and a new extra column: the derived variable, as indicated in tgt_var.

• If the target dataset is provided, then it is merged with the raw data set raw_dat by the variables indicated in id_vars, with a new column: the derived variable, as indicated in tgt_var.

Arguments

tgt_dat

Target dataset: a data frame to be merged against raw_dat by the variables indicated in id_vars. This parameter is optional, see section Value for how the output changes depending on this argument value.

tgt_var

The target SDTM variable: a single string indicating the name of variable to be derived.

raw_dat

The raw dataset (dataframe); must include the variables passed in id_vars and raw_var.

raw_var

The raw variable(s): a character vector indicating the name(s) of the raw variable(s) in raw_dat with date or time components to be parsed into a ISO8601 format variable in tgt_var.

raw_fmt

A date/time parsing format. Either a character vector or a list of character vectors. If a character vector is passed then each element is taken as parsing format for each variable indicated in raw_var. If a list is provided, then each element must be a character vector of formats. The first vector of formats is used for parsing the first variable in raw_var, and so on.

raw_unk

A character vector of string literals to be regarded as missing values during parsing.

id_vars

Key variables to be used in the join between the raw dataset (raw_dat) and the target data set (tgt_dat).

.warn

Whether to warn about parsing failures.

Examples

# `md1`: an example raw data set.
md1 <-
  tibble::tribble(
    ~oak_id, ~raw_source, ~patient_number, ~MDBDR,        ~MDEDR,        ~MDETM,
    1L,      "MD1",       375,             NA,            NA,            NA,
    2L,      "MD1",       375,             "15-Sep-20",   NA,            NA,
    3L,      "MD1",       376,             "17-Feb-21",   "17-Feb-21",   NA,
    4L,      "MD1",       377,             "4-Oct-20",    NA,            NA,
    5L,      "MD1",       377,             "20-Jan-20",   "20-Jan-20",   "10:00:00",
    6L,      "MD1",       377,             "UN-UNK-2019", "UN-UNK-2019", NA,
    7L,      "MD1",       377,             "20-UNK-2019", "20-UNK-2019", NA,
    8L,      "MD1",       378,             "UN-UNK-2020", "UN-UNK-2020", NA,
    9L,      "MD1",       378,             "26-Jan-20",   "26-Jan-20",   "07:00:00",
    10L,     "MD1",       378,             "28-Jan-20",   "1-Feb-20",    NA,
    11L,     "MD1",       378,             "12-Feb-20",   "18-Feb-20",   NA,
    12L,     "MD1",       379,             "10-UNK-2020", "20-UNK-2020", NA,
    13L,     "MD1",       379,             NA,            NA,            NA,
    14L,     "MD1",       379,             NA,            "17-Feb-20",   NA
  )

# Using the raw data set `md1`, derive the variable CMSTDTC from MDBDR using
# the parsing format (`raw_fmt`) `"d-m-y"` (day-month-year), while allowing
# for the presence of special date component values (e.g. `"UN"` or `"UNK"`),
# indicating that these values are missing/unknown (unk).
cm1 <-
  assign_datetime(
    tgt_var = "CMSTDTC",
    raw_dat = md1,
    raw_var = "MDBDR",
    raw_fmt = "d-m-y",
    raw_unk = c("UN", "UNK")
  )

cm1

# Inspect parsing failures associated with derivation of CMSTDTC.
problems(cm1$CMSTDTC)

# `cm_inter`: an example target data set.
cm_inter <-
  tibble::tibble(
    oak_id = 1L:14L,
    raw_source = "MD1",
    patient_number = c(
      375, 375, 376, 377, 377, 377, 377, 378,
      378, 378, 378, 379, 379, 379
    ),
    CMTRT = c(
      "BABY ASPIRIN",
      "CORTISPORIN",
      "ASPIRIN",
      "DIPHENHYDRAMINE HCL",
      "PARCETEMOL",
      "VOMIKIND",
      "ZENFLOX OZ",
      "AMITRYPTYLINE",
      "BENADRYL",
      "DIPHENHYDRAMINE HYDROCHLORIDE",
      "TETRACYCLINE",
      "BENADRYL",
      "SOMINEX",
      "ZQUILL"
    ),
    CMINDC = c(
      "NA",
      "NAUSEA",
      "ANEMIA",
      "NAUSEA",
      "PYREXIA",
      "VOMITINGS",
      "DIARHHEA",
      "COLD",
      "FEVER",
      "LEG PAIN",
      "FEVER",
      "COLD",
      "COLD",
      "PAIN"
    )
  )

# Same derivation as above but now involving the merging with the target
# data set `cm_inter`.
cm2 <-
  assign_datetime(
    tgt_dat = cm_inter,
    tgt_var = "CMSTDTC",
    raw_dat = md1,
    raw_var = "MDBDR",
    raw_fmt = "d-m-y"
  )

cm2

# Inspect parsing failures associated with derivation of CMSTDTC.
problems(cm2$CMSTDTC)

# Derive CMSTDTC using both MDEDR and MDETM variables.
# Note that the format `"d-m-y"` is used for parsing MDEDR and `"H:M:S"` for
# MDETM (correspondence is by positional matching).
cm3 <-
  assign_datetime(
    tgt_var = "CMSTDTC",
    raw_dat = md1,
    raw_var = c("MDEDR", "MDETM"),
    raw_fmt = c("d-m-y", "H:M:S"),
    raw_unk = c("UN", "UNK")
  )

cm3

# Inspect parsing failures associated with derivation of CMSTDTC.
problems(cm3$CMSTDTC)