simaerep (version 0.7.0)

get_config: Get Portfolio Configuration

Description

Get Portfolio configuration from a dataframe aggregated on patient level with max_ae and max_visit. Will filter studies with only a few sites and patients and will anonymize IDs. Portfolio configuration can be used by sim_test_data_portfolio to generate data for an artificial portfolio.

Usage

get_config(
  df_site,
  min_pat_per_study = 100,
  min_sites_per_study = 10,
  anonymize = TRUE,
  pad_width = 4
)

Value

dataframe with the following columns:

study_id

study identification

ae_per_visit_mean

mean AE per visit per study

site_number

site

max_visit_sd

standard deviation of maximum patient visits per site

max_visit_mean

mean of maximum patient visits per site

n_pat

number of patients

Arguments

df_site

dataframe aggregated on patient level with max_ae and max_visit

min_pat_per_study

minimum number of patients per study, Default: 100

min_sites_per_study

minimum number of sites per study, Default: 10

anonymize

logical, Default: TRUE

pad_width

padding width for newly created IDs, Default: 4

See Also

sim_test_data_study get_config sim_test_data_portfolio sim_ur_scenarios get_portf_perf

Examples

# \donttest{
df_visit1 <- sim_test_data_study(n_pat = 100, n_sites = 10,
                                 frac_site_with_ur = 0.4, ur_rate = 0.6)

df_visit1$study_id <- "A"

df_visit2 <- sim_test_data_study(n_pat = 100, n_sites = 10,
                                 frac_site_with_ur = 0.2, ur_rate = 0.1)

df_visit2$study_id <- "B"

df_visit <- dplyr::bind_rows(df_visit1, df_visit2)

df_site_max <- df_visit %>%
  dplyr::group_by(study_id, site_number, patnum) %>%
  dplyr::summarise(max_visit = max(visit),
            max_ae = max(n_ae),
            .groups = "drop")

df_config <- get_config(df_site_max)

df_config

df_portf <- sim_test_data_portfolio(df_config)

df_portf

df_scen <- sim_ur_scenarios(df_portf,
                            extra_ur_sites = 2,
                            ur_rate = c(0.5, 1))


df_scen

df_perf <- get_portf_perf(df_scen)

df_perf
# }