requireDemographics() filters cohort records, keeping only records where
individuals satisfy the specified demographic criteria.
Arguments
- cohort
A cohort table in a cdm reference.
- 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.
- indexDate
Variable in cohort that contains the date to compute the demographics characteristics on which to restrict on.
- ageRange
A list of vectors specifying minimum and maximum age.
- sex
Can be "Both", "Male" or "Female".
- minPriorObservation
A minimum number of continuous prior observation days in the database.
- minFutureObservation
A minimum number of continuous future observation days in the database.
- 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.
Examples
# \donttest{
library(CohortConstructor)
cdm <- mockCohortConstructor()
#> Warning: '/tmp/RtmpPEGCev/id_qvh' already exists
#> ℹ Reading GiBleed tables.
cdm$cohort1 |>
requireDemographics(indexDate = "cohort_start_date",
ageRange = list(c(18, 65)),
sex = "Female",
minPriorObservation = 365)
#> # A tibble: 11 × 4
#> cohort_definition_id subject_id cohort_start_date cohort_end_date
#> * <int> <int> <date> <date>
#> 1 1 2 2016-10-22 2017-09-09
#> 2 1 9 2016-01-11 2017-12-06
#> 3 1 23 1998-08-13 1998-11-14
#> 4 1 50 2013-03-26 2016-11-30
#> 5 1 51 2015-09-24 2015-10-30
#> 6 1 54 2004-03-03 2005-12-19
#> 7 1 58 1999-03-08 2002-10-02
#> 8 1 60 2012-02-11 2014-01-26
#> 9 1 65 2019-01-01 2019-08-24
#> 10 1 70 1997-11-14 1998-01-15
#> 11 1 72 2016-07-23 2017-09-13
# }