Sample Longitudinal Counts Data

Builds a pre-aggregated summary data frame of patient and measurement counts at discrete follow-up time windows. The counts are derived by binning the continuous time column from sample_spaghetti_data(), so the two functions share the same underlying simulation.

Usage

sample_longitudinal_counts_data(n_patients = 300, max_obs = 6, seed = 42L)

Arguments

n_patients

Number of unique patients passed to sample_spaghetti_data(). Default 300.

max_obs

Maximum observations per patient passed to sample_spaghetti_data(). Default 6.

seed

Random seed. Default 42.

Value

A data frame in long format with columns:

• time_label — ordered factor of follow-up windows

• series — "Patients" or "Measurements"

• count — integer count

See also

hv_longitudinal(), sample_spaghetti_data()

Examples

dta <- sample_longitudinal_counts_data(n_patients = 300, seed = 42)
str(dta)                # time_label (factor), series, count
#> 'data.frame':	14 obs. of  3 variables:
#>  $ time_label: Factor w/ 7 levels "≥0 Days","≥1 Month",..: 1 2 3 4 5 6 7 1 2 3 ...
#>  $ series    : chr  "Patients" "Patients" "Patients" "Patients" ...
#>  $ count     : int  19 47 49 100 159 101 276 19 50 56 ...
levels(dta$time_label)  # 7 discrete follow-up windows
#> [1] "≥0 Days"    "≥1 Month"   "≥3 Months"  "≥6 Months"  "≥1 Year"   
#> [6] "≥2 Years"   "≥2.5 Years"

# Inspect patient counts at each window
subset(dta, series == "Patients")
#>   time_label   series count
#> 1    ≥0 Days Patients    19
#> 2   ≥1 Month Patients    47
#> 3  ≥3 Months Patients    49
#> 4  ≥6 Months Patients   100
#> 5    ≥1 Year Patients   159
#> 6   ≥2 Years Patients   101
#> 7 ≥2.5 Years Patients   276

# Larger cohort
dta2 <- sample_longitudinal_counts_data(n_patients = 1000, seed = 7)
max(dta2$count)         # peak observation count
#> [1] 2006