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.
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
)The input dataset with the datetime *DTM (and the date/time imputation
flag *DTF, *TMF) added.
Input dataset
The variables specified by the dtc argument are expected to be in the dataset.
a dataset, i.e., a data.frame or tibble
none
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.
a character scalar, i.e., a character vector of length one
none
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.
a character date variable
none
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.
"Y" (year, highest level), "M" (month), "D"
(day), "h" (hour), "m" (minute), "s" (second), "n" (none, lowest
level)
"h"
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).
"first", "mid", "last", or user-defined
"first"
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".
"first", "last", or user-defined
"first"
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.
"auto", "date","time", "both" or "none"
"auto"
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.
a list of dates, e.g. list(ymd_hms("2021-07-01T04:03:01"), ymd_hms("2022-05-12T13:57:23"))
NULL
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.
a list of dates, e.g. list(ymd_hms("2021-07-01T04:03:01"), ymd_hms("2022-05-12T13:57:23"))
NULL
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").
"TRUE", "FALSE"
FALSE
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.
"TRUE", "FALSE"
FALSE
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>
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> 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 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
"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)
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 example usages of this function can be found in the Date and Time Imputation vignette.
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.
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()