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Derive/Impute a Datetime from a Character Date

Source: R/derive_vars_dtm.R
derive_vars_dtm.Rd

Derive a datetime object (*DTM) from a character date (--DTC). The date and time can be imputed (see date_imputation/time_imputation arguments) and the date/time imputation flag (*DTF, *TMF) can be added.

Usage 

derive_vars_dtm(
  dataset,
  new_vars_prefix,
  dtc,
  highest_imputation = "h",
  date_imputation = "first",
  time_imputation = "first",
  flag_imputation = "auto",
  min_dates = NULL,
  max_dates = NULL,
  preserve = FALSE,
  ignore_seconds_flag = FALSE
)

Arguments

dataset

Input dataset

The variables specified by the dtc argument are expected to be in the dataset.

Permitted values

a dataset, i.e., a data.frame or tibble

Default value

none

new_vars_prefix

Prefix used for the output variable(s).

A character scalar is expected. For the date variable (*DT) is appended to the specified prefix, for the date imputation flag (*DTF), and for the time imputation flag (*TMF), i.e., for new_vars_prefix = "AST" the variables ASTDT, ASTDTF, and ASTTMF are created.

Permitted values

a character scalar, i.e., a character vector of length one

Default value

none

dtc

The --DTC date to impute

A character date is expected in a format like yyyy-mm-dd or yyyy-mm-ddThh:mm:ss. Trailing components can be omitted and - is a valid "missing" value for any component.

Permitted values

a character date variable

Default value

none

highest_imputation

Highest imputation level

The highest_imputation argument controls which components of the DTC value are imputed if they are missing. All components up to the specified level are imputed.

If a component at a higher level than the highest imputation level is missing, NA_character_ is returned. For example, for highest_imputation = "D" "2020" results in NA_character_ because the month is missing.

If "n" is specified, no imputation is performed, i.e., if any component is missing, NA_character_ is returned.

If "Y" is specified, date_imputation should be "first" or "last" and min_dates or max_dates should be specified respectively. Otherwise, NA_character_ is returned if the year component is missing.

Permitted values

"Y" (year, highest level), "M" (month), "D" (day), "h" (hour), "m" (minute), "s" (second), "n" (none, lowest level)

Default value

"h"

date_imputation

The value to impute the day/month when a datepart is missing.

A character value is expected.

  • If highest_imputation is "M", month and day can be specified as "mm-dd": e.g. "06-15" for the 15th of June

  • When highest_imputation is "M" or "D", the following keywords are available: "first", "mid", "last" to impute to the first/mid/last day/month. If "mid" is specified, missing components are imputed as the middle of the possible range:

    • If both month and day are missing, they are imputed as "06-30" (middle of the year).

    • If only day is missing, it is imputed as "15" (middle of the month).

The year can not be specified; for imputing the year "first" or "last" together with min_dates or max_dates argument can be used (see examples).

Permitted values

"first", "mid", "last", or user-defined

Default value

"first"

time_imputation

The value to impute the time when a timepart is missing.

A character value is expected, either as a

  • format with hour, min and sec specified as "hh:mm:ss": e.g. "00:00:00" for the start of the day,

  • or as a keyword: "first","last" to impute to the start/end of a day.

The argument is ignored if highest_imputation = "n".

Permitted values

"first", "last", or user-defined

Default value

"first"

flag_imputation

Whether the date/time imputation flag(s) must also be derived.

If "both" or "date" is specified, then date imputation flag is derived. If "auto" is specified and highest_imputation argument is greater than "h", then date imputation flag is derived.

If "both" or "time" is specified, then time imputation flag is derived. If "auto" is specified and highest_imputation argument is not "n", then time imputation flag is derived.

If "none" is specified, then no date or time imputation flag is derived.

Please note that CDISC requirements dictate the need for a date/time imputation flag if any imputation is performed, so flag_imputation = "none" should only be used if the imputed variable is not part of the final ADaM dataset.

Permitted values

"auto", "date","time", "both" or "none"

Default value

"auto"

min_dates

Minimum dates

A list of dates is expected. It is ensured that the imputed date is not before any of the specified dates, e.g., that the imputed adverse event start date is not before the first treatment date. Only dates which are in the range of possible dates of the dtc value are considered. The possible dates are defined by the missing parts of the dtc date (see example below). This ensures that the non-missing parts of the dtc date are not changed. A date or date-time object is expected. For example

impute_dtc_dtm(
  "2020-11",
  min_dates = list(
   ymd_hms("2020-12-06T12:12:12"),
   ymd_hms("2020-11-11T11:11:11")
  ),
  highest_imputation = "M"
)

returns "2020-11-11T11:11:11" because the possible dates for "2020-11" range from "2020-11-01T00:00:00" to "2020-11-30T23:59:59". Therefore "2020-12-06T12:12:12" is ignored. Returning "2020-12-06T12:12:12" would have changed the month although it is not missing (in the dtc date).

For date variables (not datetime) in the list the time is imputed to "00:00:00". Specifying date variables makes sense only if the date is imputed. If only time is imputed, date variables do not affect the result.

Permitted values

a list of dates, e.g. list(ymd_hms("2021-07-01T04:03:01"), ymd_hms("2022-05-12T13:57:23"))

Default value

NULL

max_dates

Maximum dates

A list of dates is expected. It is ensured that the imputed date is not after any of the specified dates, e.g., that the imputed date is not after the data cut off date. Only dates which are in the range of possible dates are considered. A date or date-time object is expected.

For date variables (not datetime) in the list the time is imputed to "23:59:59". Specifying date variables makes sense only if the date is imputed. If only time is imputed, date variables do not affect the result.

Permitted values

a list of dates, e.g. list(ymd_hms("2021-07-01T04:03:01"), ymd_hms("2022-05-12T13:57:23"))

Default value

NULL

preserve

Preserve lower level date/time part when higher order part is missing, e.g. preserve day if month is missing or preserve minute when hour is missing.

For example "2019---07" would return "2019-06-07 if preserve = TRUE (and date_imputation = "mid").

Permitted values

"TRUE", "FALSE"

Default value

FALSE

ignore_seconds_flag

ADaM IG states that given SDTM (--DTC) variable, if only hours and minutes are ever collected, and seconds are imputed in (*DTM) as 00, then it is not necessary to set (*TMF) to "S". A user can set this to TRUE so the "S" Flag is dropped from (*TMF).

Please note that the default value of ignore_seconds_flag will change to TRUE in admiral 1.4.0.

Permitted values

"TRUE", "FALSE"

Default value

FALSE

Value

The input dataset with the datetime *DTM (and the date/time imputation flag *DTF, *TMF) added.

Details

In {admiral} we don't allow users to pick any single part of the date/time to impute, we only enable to impute up to a highest level, i.e. you couldn't choose to say impute months, but not days.

The presence of a *DTF variable is checked and the variable is not derived if it already exists in the input dataset. However, if *TMF already exists in the input dataset, a warning is issued and *TMF will be overwritten.

See also

Date/Time Derivation Functions that returns variable appended to dataset: derive_var_trtdurd(), derive_vars_dt(), derive_vars_dtm_to_dt(), derive_vars_dtm_to_tm(), derive_vars_duration(), derive_vars_dy()

Examples

Derive a datetime variable imputing time

In this example, we derive ASTDTM from MHSTDTC. Note that by default the function imputes missing time components to 00 but doesn't impute missing date components and automatically produces the time imputation flag (ASTTMF).

library(tibble)
library(lubridate)

mhdt <- tribble(
  ~MHSTDTC,
  "2019-07-18T15:25:40",
  "2019-07-18T15:25",
  "2019-07-18",
  "2019-02",
  "2019",
  "2019---07",
  ""
)

derive_vars_dtm(
  mhdt,
  new_vars_prefix = "AST",
  dtc = MHSTDTC
)
#> # A tibble: 7 × 3
#>   MHSTDTC               ASTDTM              ASTTMF
#>   <chr>                 <dttm>              <chr>
#> 1 "2019-07-18T15:25:40" 2019-07-18 15:25:40 <NA>
#> 2 "2019-07-18T15:25"    2019-07-18 15:25:00 S
#> 3 "2019-07-18"          2019-07-18 00:00:00 H
#> 4 "2019-02"             NA                  <NA>
#> 5 "2019"                NA                  <NA>
#> 6 "2019---07"           NA                  <NA>
#> 7 ""                    NA                  <NA>

Impute to the latest (date_imputation = "last")

In this example, we set date_imputation = "last" to get the last month/day for partial dates. We also set time_imputation = "last". The function will use all or part of 23:59:59 for time imputation. Note that highest_imputation must be at least "D" to perform date imputation. Here we use highest_imputation = "M" to request imputation of month and day (and time). Also note that two flag variables are created.

derive_vars_dtm(
 mhdt,
 new_vars_prefix = "AST",
 dtc = MHSTDTC,
 date_imputation = "last",
 time_imputation = "last",
 highest_imputation = "M"
)
#> # A tibble: 7 × 4
#>   MHSTDTC               ASTDTM              ASTDTF ASTTMF
#>   <chr>                 <dttm>              <chr>  <chr>
#> 1 "2019-07-18T15:25:40" 2019-07-18 15:25:40 <NA>   <NA>
#> 2 "2019-07-18T15:25"    2019-07-18 15:25:59 <NA>   S
#> 3 "2019-07-18"          2019-07-18 23:59:59 <NA>   H
#> 4 "2019-02"             2019-02-28 23:59:59 D      H
#> 5 "2019"                2019-12-31 23:59:59 M      H
#> 6 "2019---07"           2019-12-31 23:59:59 M      H
#> 7 ""                    NA                  <NA>   <NA>

Suppress imputation flags (flag_imputation = "none")

In this example, we derive ASTDTM but suppress the ASTTMF. Note that function appends missing "hh:mm:ss" to ASTDTM. The flag_imputation = "none" call ensures no date/time imputation flag is created. In practice, as per CDISC requirements this option can only be selected if the imputed variable is not part of the final ADaM dataset.

derive_vars_dtm(
  mhdt,
  new_vars_prefix = "AST",
  dtc = MHSTDTC,
  flag_imputation = "none"
)
#> # A tibble: 7 × 2
#>   MHSTDTC               ASTDTM
#>   <chr>                 <dttm>
#> 1 "2019-07-18T15:25:40" 2019-07-18 15:25:40
#> 2 "2019-07-18T15:25"    2019-07-18 15:25:00
#> 3 "2019-07-18"          2019-07-18 00:00:00
#> 4 "2019-02"             NA
#> 5 "2019"                NA
#> 6 "2019---07"           NA
#> 7 ""                    NA

Avoid imputation after specified datetimes (max_dates)

In this example, we derive AENDTM where AE end date is imputed to the last date. To ensure that the imputed date is not after the death or data cut off date we can set max_dates = exprs(DTHDT, DCUTDT). Note two flag variables: ASTDTF and ASTTMF are created. Setting highest_imputation = "Y" will allow for the missing AEENDTC record to be imputed from max_dates = exprs(DTHDT, DCUTDT).

adae <- tribble(
   ~AEENDTC,             ~DTHDT,           ~DCUTDT,
   "2020-12", ymd("2020-12-26"), ymd("2020-12-24"),
   "2020-11", ymd("2020-12-06"), ymd("2020-12-24"),
          "", ymd("2020-12-06"), ymd("2020-12-24"),
"2020-12-20", ymd("2020-12-06"), ymd("2020-12-24")
)

derive_vars_dtm(
  adae,
  dtc = AEENDTC,
  new_vars_prefix = "AEN",
  highest_imputation = "Y",
  date_imputation = "last",
  time_imputation = "last",
  max_dates = exprs(DTHDT, DCUTDT)
)
#> # A tibble: 4 × 6
#>   AEENDTC      DTHDT      DCUTDT     AENDTM              AENDTF AENTMF
#>   <chr>        <date>     <date>     <dttm>              <chr>  <chr>
#> 1 "2020-12"    2020-12-26 2020-12-24 2020-12-24 23:59:59 D      H
#> 2 "2020-11"    2020-12-06 2020-12-24 2020-11-30 23:59:59 D      H
#> 3 ""           2020-12-06 2020-12-24 2020-12-06 23:59:59 Y      H
#> 4 "2020-12-20" 2020-12-06 2020-12-24 2020-12-20 23:59:59 <NA>   H

Suppress "S" for imputation flag (ignore_seconds_flag)

In this example, we set ignore_seconds_flag = TRUE to suppress S for seconds in the ASTTMF variable. The ADaM IG states that given SDTM (--DTC) variable, if only hours and minutes are ever collected, and seconds are imputed in (*DTM) as 00, then it is not necessary to set (*TMF) to "S".


mhdt <- tribble(
~MHSTDTC,
"2019-07-18T15:25",
"2019-07-18",
"2019-02",
"2019",
"2019---07",
""
)

derive_vars_dtm(
  mhdt,
  new_vars_prefix = "AST",
  dtc = MHSTDTC,
  highest_imputation = "M",
  ignore_seconds_flag = TRUE
)
#> # A tibble: 6 × 4
#>   MHSTDTC            ASTDTM              ASTDTF ASTTMF
#>   <chr>              <dttm>              <chr>  <chr>
#> 1 "2019-07-18T15:25" 2019-07-18 15:25:00 <NA>   <NA>
#> 2 "2019-07-18"       2019-07-18 00:00:00 <NA>   H
#> 3 "2019-02"          2019-02-01 00:00:00 D      H
#> 4 "2019"             2019-01-01 00:00:00 M      H
#> 5 "2019---07"        2019-01-01 00:00:00 M      H
#> 6 ""                 NA                  <NA>   <NA>

Preserve lower components if higher ones were imputed (preserve)

In this example, we impute dates as the middle month/day with date_imputation = "mid" and impute time as last (23:59:59) with time_imputation = "last". We use the preserve argument to "preserve" partial dates. For example, "2019---18T15:-:05", will be displayed as "2019-06-18 15:59:05" by setting preserve = TRUE.

mhdt <- tribble(
~MHSTDTC,
"2019-07-18T15:25",
"2019---18T15:-:05",
"2019-07-18",
"2019-02",
"2019",
"2019---07",
""
)

derive_vars_dtm(
  mhdt,
  new_vars_prefix = "AST",
  dtc = MHSTDTC,
  highest_imputation = "M",
  date_imputation = "mid",
  time_imputation = "last",
  preserve = TRUE
)
#> # A tibble: 7 × 4
#>   MHSTDTC             ASTDTM              ASTDTF ASTTMF
#>   <chr>               <dttm>              <chr>  <chr>
#> 1 "2019-07-18T15:25"  2019-07-18 15:25:59 <NA>   S
#> 2 "2019---18T15:-:05" 2019-06-18 15:59:05 M      M
#> 3 "2019-07-18"        2019-07-18 23:59:59 <NA>   H
#> 4 "2019-02"           2019-02-15 23:59:59 D      H
#> 5 "2019"              2019-06-30 23:59:59 M      H
#> 6 "2019---07"         2019-06-07 23:59:59 M      H
#> 7 ""                  NA                  <NA>   <NA>

Further examples

Further example usages of this function can be found in the Date and Time Imputation vignette.