
Set cohort end date to the first of a set of column dates
Source:R/exitAtColumnDate.R
exitAtFirstDate.RdexitAtFirstDate() resets cohort end date based on a set of specified
column dates. The first date that occurs is chosen.
Usage
exitAtFirstDate(
cohort,
dateColumns,
cohortId = NULL,
returnReason = FALSE,
keepDateColumns = TRUE,
name = tableName(cohort),
.softValidation = FALSE
)Arguments
- cohort
A cohort table in a cdm reference.
- dateColumns
Character vector indicating date columns in the cohort table to consider.
- cohortId
Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
- returnReason
If TRUE it will return a column indicating which of the
dateColumnswas used.- keepDateColumns
If TRUE the returned cohort will keep columns in
dateColumns.- name
Name of the new cohort table created in the cdm object.
- .softValidation
Whether to perform a soft validation of consistency. If set to FALSE four additional checks will be performed: 1) a check that cohort end date is not before cohort start date, 2) a check that there are no missing values in required columns, 3) a check that cohort duration is all within observation period, and 4) that there are no overlapping cohort entries
Examples
# \donttest{
library(CohortConstructor)
library(PatientProfiles)
cdm <- mockCohortConstructor()
#> ℹ Reading GiBleed tables.
cdm$cohort1 <- cdm$cohort1 |>
addTableIntersectDate(tableName = "observation", nameStyle = "next_obs", order = "first") |>
addFutureObservation(futureObservationType = "date", name = "cohort1")
cdm$cohort1 |>
exitAtFirstDate(dateColumns = c("next_obs", "future_observation"))
#> Joining with `by = join_by(cohort_definition_id, subject_id,
#> cohort_start_date)`
#> # A tibble: 63 × 6
#> cohort_definition_id subject_id cohort_start_date cohort_end_date next_obs
#> <int> <int> <date> <date> <date>
#> 1 1 1 2001-08-27 2002-03-01 2002-03-01
#> 2 1 2 2004-02-28 2004-11-16 2004-11-16
#> 3 1 4 2014-12-22 2015-08-12 2015-08-12
#> 4 1 5 1956-09-11 1956-09-29 1956-09-29
#> 5 1 6 2015-01-04 2015-01-13 2015-01-13
#> 6 1 7 1969-08-13 1969-09-13 1969-09-13
#> 7 1 11 2018-03-14 2018-04-04 NA
#> 8 1 12 2004-11-10 2005-08-13 2005-08-13
#> 9 1 13 1993-09-23 1993-09-23 1993-09-23
#> 10 1 14 1990-06-10 1991-06-13 1991-06-13
#> # ℹ 53 more rows
#> # ℹ 1 more variable: future_observation <date>
# }