simulate under-reporting

we remove a fraction of events from a specific site

Usage

sim_out(df_visit, study_id, site_id, factor_event)

Arguments

df_visit,

dataframe

study_id,

character

site_id,

character

factor_event,

double, negative values for under-reporting positive for for over-reporting.

Details

we determine the absolute number of events per patient for removal. Then them remove them at the first visit. We intentionally allow fractions

Examples

df_visit <- sim_test_data_study(n_pat = 100, n_sites = 10)


df_ur <- sim_out(df_visit, "A", site_id = "S0001", factor_event = - 0.35)

# Example cumulated event for first patient with 35% under-reporting
df_ur[df_ur$site_id == "S0001" & df_ur$patient_id == "P000001",]$n_event
#>  [1] 0.0 0.0 0.0 0.5 1.5 2.5 3.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5
#> [20] 4.5 6.5 6.5 6.5 6.5

# Example cumulated event for first patient with no under-reporting
df_visit[df_visit$site_id == "S0001" & df_visit$patient_id == "P000001",]$n_event
#>  [1]  0  2  2  4  5  6  7  8  8  8  8  8  8  8  8  8  8  8  8  8 10 10 10 10