requireSex() filters cohort records, keeping only records where individuals
satisfy the specified sex criteria.
Usage
requireSex(
cohort,
sex,
cohortId = NULL,
atFirst = FALSE,
name = tableName(cohort),
.softValidation = TRUE
)Arguments
- cohort
A cohort table in a cdm reference.
- sex
Can be "Both", "Male" or "Female".
- 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.
- atFirst
If FALSE the requirement will be applied to all records, if TRUE, it will only be required for the first entry of each subject.
- 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)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
requireSex(sex = "Female")
#> # Source: table<cohort1> [?? x 4]
#> # Database: DuckDB v1.3.1 [unknown@Linux 6.11.0-1015-azure:R 4.5.1/:memory:]
#> cohort_definition_id subject_id cohort_start_date cohort_end_date
#> <int> <int> <date> <date>
#> 1 1 2 2010-03-30 2010-04-20
#> 2 1 3 2007-07-10 2007-11-24
#> 3 1 4 2017-05-07 2017-07-06
#> 4 1 5 2016-11-01 2016-12-06
#> 5 1 9 2007-03-19 2007-09-15
#> 6 1 3 2007-04-25 2007-07-09
#> 7 1 5 2016-08-28 2016-10-13
#> 8 1 3 2005-09-25 2007-04-24
# }