Create a fake subject database with clustering
Source:R/FakePatientsDB.R
create_fake_subjectDB_clustered.Rd
Create a fake subject database with clustering
Usage
create_fake_subjectDB_clustered(
n_subjects = 50,
n_facilities = 10,
avg_n_stays = 3,
days_since_discharge = NULL,
length_of_stay = NULL,
n_clusters = 3
)
Arguments
- n_subjects
the number of different subjects in the database
- n_facilities
the number of facility present in the database
- avg_n_stays
the average number of stays per subject
- days_since_discharge
the number of days between a discharge date and an admission date (default: max(0, rnorm(1, mean = 30, sd = 10)))
- length_of_stay
the length of stay (default: max(1, rnorm(1, mean = 5, sd = 3) )
- n_clusters
the number of cluster in the network
Examples
mydb <- create_fake_subjectDB_clustered(n_subjects = 100, n_facilities = 10)
mydb
#> sID fID Adate Ddate
#> <char> <char> <POSc> <POSc>
#> 1: s01 f8 2019-02-04 2019-02-11
#> 2: s02 f9 2019-01-26 2019-02-05
#> 3: s02 f9 2019-03-17 2019-03-24
#> 4: s02 f2 2019-04-07 2019-04-10
#> 5: s03 f9 2019-02-04 2019-02-13
#> ---
#> 266: s86 f2 2019-04-12 2019-04-24
#> 267: s90 f6 2019-06-28 2019-07-07
#> 268: s96 f6 2019-04-25 2019-05-03
#> 269: s97 f3 2019-05-23 2019-05-31
#> 270: s94 f8 2019-05-04 2019-05-08