eval_sites_deprecated {simaerep}

Evaluate sites.

Description

Correct under-reporting probabilities by the expected number of false positives (fp). This has been deprecated in favor of more conventional methods available via p.adjust.

Usage

eval_sites_deprecated(df_sim_sites, r_sim_sites)

Arguments

df_sim_sites

dataframe generated by sim_sites()

r_sim_sites

integer, number of repeats for bootstrap resampling for site simulation, needed for zero probability correction for fp calculation, Default: 1000

Details

If by chance expected number of false positives (fp) is greater than the total number of positives (p) we set p_vs_fp_ratio = 1 and prob_ur = 0.

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_low

bootstrapped probability for having mean_ae_site_med75 or lower

n_site

number of study sites

pval_n_detected

sites with the same p-value or lower

pval_fp

expected number of fp, pval * n_site

pval_p_vs_fp_ratio

odds under-reporting as p/fp, poisson.test (use as benchmark)

pval_prob_ur

probability under-reporting as 1 - fp/p, poisson.test (use as benchmark)

prob_low_n_detected

sites with same bootstrapped probability or lower

prob_low_fp

expected number of fp, prob_lower * n_site

prob_low_p_vs_fp_ratio

odds under-reporting as p/fp, bootstrapped (use)

prob_low_prob_ur

probability under-reporting as 1 - fp/p, bootstrapped (use)

See Also

site_aggr(), sim_sites()

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_site <- site_aggr(df_visit)

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

df_eval <- eval_sites_deprecated(df_sim_sites, r_sim_sites = 100)
df_eval