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Imputation partial date portion of a '--DTC' variable based on user input.

Usage

impute_dtc_dt(
  dtc,
  highest_imputation = "n",
  date_imputation = "first",
  min_dates = NULL,
  max_dates = NULL,
  preserve = FALSE
)

Arguments

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: "n"

Permitted Values: "Y" (year, highest level), "M" (month), "D" (day), "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"

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).

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.

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

Value

A character vector

Details

Usually this computation function can not be used with %>%.

See also

Date/Time Computation Functions that returns a vector: compute_dtf(), compute_duration(), compute_tmf(), convert_date_to_dtm(), convert_dtc_to_dtm(), convert_dtc_to_dt(), impute_dtc_dtm()

Examples

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_dtm(
  dtc = dates,
  highest_imputation = "M",
  date_imputation = "01-01"
)
#> [1] "2019-07-18T15:25:40" "2019-07-18T15:25:00" "2019-07-18T15:00:00"
#> [4] "2019-07-18T00:00:00" "2019-02-01T00:00:00" "2019-01-01T00:00:00"
#> [7] "2019-01-01T00:00:00" "2019-01-01T00:00:00" 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"