trimDemographics() resets the cohort start and end date based on the
specified demographic criteria is satisfied.
Usage
trimDemographics(
cohort,
cohortId = NULL,
ageRange = NULL,
sex = NULL,
minPriorObservation = NULL,
minFutureObservation = NULL,
name = tableName(cohort)
)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.
- 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.
- name
Name of the new cohort table created in the cdm object.
Examples
# \donttest{
library(CohortConstructor)
cdm <- mockCohortConstructor(nPerson = 100)
cdm$cohort1 |> trimDemographics(ageRange = list(c(10, 30)))
#> ℹ Building new trimmed cohort
#> Adding demographics information
#> Creating initial cohort
#> Trim age
#> ✔ Cohort trimmed
#> # Source: table<main.cohort1> [?? x 4]
#> # Database: DuckDB v1.1.3 [unknown@Linux 6.8.0-1017-azure:R 4.4.2/:memory:]
#> cohort_definition_id subject_id cohort_start_date cohort_end_date
#> <int> <int> <date> <date>
#> 1 1 4 1998-12-14 2002-02-14
#> 2 1 9 2011-12-30 2012-04-02
#> 3 1 21 1985-08-16 1986-09-10
#> 4 1 26 1984-05-16 1989-03-22
#> 5 1 35 2007-05-13 2010-07-22
#> 6 1 39 2000-03-07 2009-03-17
#> 7 1 41 2000-11-22 2000-12-09
#> 8 1 69 2003-01-14 2003-05-28
#> 9 1 71 2009-02-01 2009-09-05
#> 10 1 83 2007-05-29 2008-05-01
#> # ℹ more rows
# }