Imputation partial date portion of a --DTC variable based on user input.
impute_dtc_dt(
dtc,
highest_imputation = "n",
date_imputation = "first",
min_dates = NULL,
max_dates = NULL,
preserve = FALSE
)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 must be "first" or "last"
and min_dates or max_dates must be specified respectively. Otherwise,
an error is thrown.
"Y" (year, highest level), "M" (month), "D"
(day), "n" (none, lowest level)
"n"
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"
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).
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.
a list of dates, e.g. list(ymd_hms("2021-07-01T04:03:01"), ymd_hms("2022-05-12T13:57:23"))
NULL
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").
"TRUE", "FALSE"
FALSE
A character vector
Usually this computation function can not be used with %>%.
Date/Time Computation Functions that returns a vector:
compute_age_years(),
compute_dtf(),
compute_duration(),
compute_tmf(),
convert_date_to_dtm(),
convert_dtc_to_dt(),
convert_dtc_to_dtm(),
impute_dtc_dtm()
library(lubridate)
dates <- c(
"2019-07-18T15:25:40",
"2019-07-18T15:25",
"2019-07-18T15",
"2019-07-18",
"2019-02",
"2019",
"2019",
"2019---07",
""
)
# No date imputation (highest_imputation defaulted to "n")
impute_dtc_dt(dtc = dates)
#> [1] "2019-07-18" "2019-07-18" "2019-07-18" "2019-07-18" NA
#> [6] NA NA NA NA
# Impute to first day/month if date is partial
impute_dtc_dt(
dtc = dates,
highest_imputation = "M"
)
#> [1] "2019-07-18" "2019-07-18" "2019-07-18" "2019-07-18" "2019-02-01"
#> [6] "2019-01-01" "2019-01-01" "2019-01-01" NA
# Same as above
impute_dtc_dt(
dtc = dates,
highest_imputation = "M",
date_imputation = "01-01"
)
#> [1] "2019-07-18" "2019-07-18" "2019-07-18" "2019-07-18" "2019-02-01"
#> [6] "2019-01-01" "2019-01-01" "2019-01-01" NA
# Impute to last day/month if date is partial
impute_dtc_dt(
dtc = dates,
highest_imputation = "M",
date_imputation = "last",
)
#> [1] "2019-07-18" "2019-07-18" "2019-07-18" "2019-07-18" "2019-02-28"
#> [6] "2019-12-31" "2019-12-31" "2019-12-31" NA
# Impute to mid day/month if date is partial
impute_dtc_dt(
dtc = dates,
highest_imputation = "M",
date_imputation = "mid"
)
#> [1] "2019-07-18" "2019-07-18" "2019-07-18" "2019-07-18" "2019-02-15"
#> [6] "2019-06-30" "2019-06-30" "2019-06-30" NA
# Impute a date and ensure that the imputed date is not before a list of
# minimum dates
impute_dtc_dt(
"2020-12",
min_dates = list(
ymd("2020-12-06"),
ymd("2020-11-11")
),
highest_imputation = "M"
)
#> [1] "2020-12-06"
# Impute completely missing dates (only possible if min_dates or max_dates is specified)
impute_dtc_dt(
c("2020-12", NA_character_),
min_dates = list(
ymd("2020-12-06", "2020-01-01"),
ymd("2020-11-11", NA)
),
highest_imputation = "Y"
)
#> [1] "2020-12-06" "2020-01-01"