Calculate prob_lower for study sites using table operations

Usage

sim_inframe(df_visit, r = 1000, df_site = NULL, event_names = c("ae"))

Arguments

df_visit: Data frame with columns: study_id, site_number, patnum, visit, n_ae.
r: Integer or tbl_object, number of repetitions for bootstrap simulation. Pass a tbl object referring to a table with one column and as many rows as desired repetitions. Default: 1000.
df_site,: dataframe as returned be site_aggr(), Will switch to visit_med75. Default: NULL
event_names: vector, contains the event names, default = "ae"

Examples

df_visit <- sim_test_data_study(
  n_pat = 100,
  n_sites = 5,
  frac_site_with_ur = 0.4,
  ur_rate = 0.6
)
df_visit$study_id <- "A"

df_sim <- sim_inframe(df_visit)
df_eval <- eval_sites(df_sim)
df_eval
#> # A tibble: 5 × 10
#>   study_id site_number events events_per_visit_site visits n_pat
#>   <chr>    <chr>        <dbl>                 <dbl>  <dbl> <int>
#> 1 A        S0001           75                 0.188    400    20
#> 2 A        S0002           75                 0.186    403    20
#> 3 A        S0003          187                 0.496    377    20
#> 4 A        S0004          180                 0.453    397    20
#> 5 A        S0005          187                 0.492    380    20
#> # ℹ 4 more variables: events_per_visit_study <dbl>, prob_low <dbl>,
#> #   prob_low_adj <dbl>, prob_low_prob_ur <dbl>