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Derive/Impute a Datetime from a Date Character Vector

Source: R/derive_date_vars.R
derive_vars_dtm.Rd

Derive a datetime object ('--DTM') from a date character vector ('--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 date character vector (dtc) must be present.

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.

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.

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.

Default: "h"

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

date_imputation

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

A character value is expected, either as a

  • format with month and day specified as "mm-dd": e.g. "06-15" for the 15th of June (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).),

  • or as a keyword: "first", "mid", "last" to impute to the first/mid/last day/month.

The argument is ignored if highest_imputation is less then "D".

Default: "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".

Default: "first".

flag_imputation

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

If "auto" is specified, the date imputation flag is derived if the date_imputation argument is not null and the time imputation flag is derived if the time_imputation argument is not null

Default: "auto"

Permitted Values: "auto", "date", "time", "both", or "none"

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.

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.

preserve

Preserve day if month is missing and day is present

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

Permitted Values: TRUE, FALSE

Default: 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').

A logical value

Default: 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_dtm_to_dt(), derive_vars_dtm_to_tm(), derive_vars_dt(), derive_vars_duration(), derive_vars_dy()

Examples

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,
  highest_imputation = "M"
)
#> # A tibble: 7 x 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 15:25:00 NA     S     
#> 3 "2019-07-18"          2019-07-18 00:00:00 NA     H     
#> 4 "2019-02"             2019-02-01 00:00:00 D      H     
#> 5 "2019"                2019-01-01 00:00:00 M      H     
#> 6 "2019---07"           2019-01-01 00:00:00 M      H     
#> 7 ""                    NA                  NA     NA    

# Impute AE end date to the last date and ensure that the imputed date is not
# after the death or data cut off date
adae <- tribble(
  ~AEENDTC, ~DTHDT, ~DCUTDT,
  "2020-12", ymd("2020-12-06"), ymd("2020-12-24"),
  "2020-11", ymd("2020-12-06"), ymd("2020-12-24")
)

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

# Seconds has been removed from the input dataset.  Function now uses
# ignore_seconds_flag to remove the 'S' from the --TMF variable.
mhdt <- tribble(
  ~MHSTDTC,
  "2019-07-18T15:25",
  "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: 7 x 4
#>   MHSTDTC            ASTDTM              ASTDTF ASTTMF
#>   <chr>              <dttm>              <chr>  <chr> 
#> 1 "2019-07-18T15:25" 2019-07-18 15:25:00 NA     NA    
#> 2 "2019-07-18T15:25" 2019-07-18 15:25:00 NA     NA    
#> 3 "2019-07-18"       2019-07-18 00:00:00 NA     H     
#> 4 "2019-02"          2019-02-01 00:00:00 D      H     
#> 5 "2019"             2019-01-01 00:00:00 M      H     
#> 6 "2019---07"        2019-01-01 00:00:00 M      H     
#> 7 ""                 NA                  NA     NA    

# A user imputing dates as middle month/day, i.e. date_imputation = "MID" can
# use preserve argument to "preserve" partial dates.  For example, "2019---07",
# will be displayed as "2019-06-07" rather than 2019-06-15 with preserve = TRUE

derive_vars_dtm(
  mhdt,
  new_vars_prefix = "AST",
  dtc = MHSTDTC,
  highest_imputation = "M",
  date_imputation = "mid",
  preserve = TRUE
)
#> # A tibble: 7 x 4
#>   MHSTDTC            ASTDTM              ASTDTF ASTTMF
#>   <chr>              <dttm>              <chr>  <chr> 
#> 1 "2019-07-18T15:25" 2019-07-18 15:25:00 NA     S     
#> 2 "2019-07-18T15:25" 2019-07-18 15:25:00 NA     S     
#> 3 "2019-07-18"       2019-07-18 00:00:00 NA     H     
#> 4 "2019-02"          2019-02-15 00:00:00 D      H     
#> 5 "2019"             2019-06-30 00:00:00 M      H     
#> 6 "2019---07"        2019-06-07 00:00:00 M      H     
#> 7 ""                 NA                  NA     NA