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Evaluate sites.

Source: R/simaerep.R
eval_sites.Rd

Correct under-reporting probabilities using p.adjust.

Usage

eval_sites(
  df_sim_sites,
  method = "BH",
  under_only = TRUE,
  visit_med75 = TRUE,
  ...
)

Arguments

df_sim_sites

dataframe generated by sim_sites or sim_inframe()

method

character, passed to stats::p.adjust(), if NULL no multiplicity correction will be made.

under_only

Logical, compute under-reporting probabilities only. only applies to the classic algorithm in which a one-sided evaluation can save computation time. Default: FALSE

visit_med75

Logical, should evaluation point visit_med75 be used. Compatible with inframe and classic version of the algorithm. Default: FALSE

...

use to pass r_sim_sites parameter to eval_sites_deprecated()

Value

dataframe with the following columns:

study_id

study identification

site_number

site identification

visit_med75

median(max(visit)) * 0.75

mean_ae_site_med75

mean AE at visit_med75 site level

mean_ae_study_med75

mean AE at visit_med75 study level

pval

p-value as returned by poisson.test

prob

bootstrapped probability

See also

site_aggr, sim_sites, sim_inframe, p.adjust

Examples

df_visit <- sim_test_data_study(
  n_pat = 100,
  n_sites = 5,
  ratio_out = 0.4,
  factor_event_rate = 0.6
  ) %>%
  # internal functions require internal column names
  dplyr::rename(
    n_ae = n_event,
    site_number = site_id,
    patnum = patient_id
  )

df_site <- site_aggr(df_visit)

df_sim_sites <- sim_sites(df_site, df_visit, r = 100)

df_eval <- eval_sites(df_sim_sites)
df_eval
#> # A tibble: 5 × 10
#>   study_id site_number n_pat n_pat_with_med75 visit_med75 mean_ae_site_med75
#>   <chr>    <chr>       <int>            <dbl>       <int>              <dbl>
#> 1 A        S0001          20               17          16               20.8
#> 2 A        S0002          20               18          15               18.6
#> 3 A        S0003          20               19          14               11.1
#> 4 A        S0004          20               19          17               11.9
#> 5 A        S0005          20               16          17               11.8
#> # ℹ 4 more variables: mean_ae_study_med75 <dbl>, n_pat_with_med75_study <int>,
#> #   pval <dbl>, prob <dbl>