Create a new cohort table from stratifying an existing one
Source:R/stratifyCohorts.R
stratifyCohorts.RdstratifyCohorts() creates new cohorts, splitting an existing cohort based
on specified columns on which to stratify on.
Usage
stratifyCohorts(
cohort,
strata,
cohortId = NULL,
removeStrata = TRUE,
name = tableName(cohort)
)Arguments
- cohort
A cohort table in a cdm reference.
- strata
A strata list that point to columns in cohort table.
- cohortId
Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set.
- removeStrata
Whether to remove strata columns from final cohort table.
- name
Name of the new cohort table created in the cdm object.
Examples
# \donttest{
library(CohortConstructor)
library(PatientProfiles)
cdm <- mockCohortConstructor()
#> ℹ Reading GiBleed tables.
cdm$my_cohort <- cdm$cohort1 |>
addAge(ageGroup = list("child" = c(0, 17), "adult" = c(18, Inf))) |>
addSex(name = "my_cohort") |>
stratifyCohorts(
strata = list("sex", c("sex", "age_group")), name = "my_cohort"
)
cdm$my_cohort
#> # A tibble: 100 × 5
#> cohort_definition_id subject_id cohort_start_date cohort_end_date age
#> * <int> <int> <date> <date> <int>
#> 1 1 1 1992-05-30 1992-07-07 8
#> 2 2 2 1986-03-15 1988-05-05 6
#> 3 1 3 1997-03-12 1997-03-14 4
#> 4 1 5 2018-12-02 2019-03-07 19
#> 5 2 6 1990-07-04 1998-06-18 23
#> 6 1 10 1985-04-08 1988-04-11 9
#> 7 2 12 2014-08-23 2016-01-13 34
#> 8 1 13 1988-10-25 1989-10-25 4
#> 9 1 14 1991-12-12 1993-09-26 39
#> 10 2 15 2007-11-16 2008-03-16 10
#> # ℹ 90 more rows
settings(cdm$my_cohort)
#> # A tibble: 6 × 8
#> cohort_definition_id cohort_name target_cohort_id target_cohort_name
#> <int> <chr> <int> <chr>
#> 1 1 cohort_1_female 1 cohort_1
#> 2 2 cohort_1_male 1 cohort_1
#> 3 3 cohort_1_female_adult 1 cohort_1
#> 4 4 cohort_1_female_child 1 cohort_1
#> 5 5 cohort_1_male_adult 1 cohort_1
#> 6 6 cohort_1_male_child 1 cohort_1
#> # ℹ 4 more variables: target_cohort_table_name <chr>, strata_columns <chr>,
#> # sex <chr>, age_group <chr>
attrition(cdm$my_cohort)
#> # A tibble: 16 × 7
#> cohort_definition_id number_records number_subjects reason_id reason
#> <int> <int> <int> <int> <chr>
#> 1 1 50 50 1 Initial qualif…
#> 2 1 18 18 2 filter strata:…
#> 3 2 50 50 1 Initial qualif…
#> 4 2 32 32 2 filter strata:…
#> 5 3 50 50 1 Initial qualif…
#> 6 3 18 18 2 filter strata:…
#> 7 3 11 11 3 filter strata:…
#> 8 4 50 50 1 Initial qualif…
#> 9 4 18 18 2 filter strata:…
#> 10 4 7 7 3 filter strata:…
#> 11 5 50 50 1 Initial qualif…
#> 12 5 32 32 2 filter strata:…
#> 13 5 18 18 3 filter strata:…
#> 14 6 50 50 1 Initial qualif…
#> 15 6 32 32 2 filter strata:…
#> 16 6 14 14 3 filter strata:…
#> # ℹ 2 more variables: excluded_records <int>, excluded_subjects <int>
# }