Reports how faithfully a synthetic cohort reproduces its seed, per variable, so a replica can be judged before it is released. Categorical columns are compared by total variation distance between their proportion tables; numeric columns by standardised difference in means and by the Kolmogorov-Smirnov statistic.
Arguments
- original
The real seed cohort.
- synthetic
A replica, e.g. from
sdt_synthesise().
Value
A tibble::tibble() with one row per shared column and statistic:
variable, type, statistic, value, and flag, which is TRUE
where the divergence exceeds a conventional 0.1 and the column deserves a
look. Returns a 0-row tibble of the same shape when nothing is shared.
Examples
seed_cohort <- sdt_synthetic_cohort(n = 80, seed = 1)
replica <- sdt_synthetic_cohort(n = 80, seed = 2)
sdt_synthesis_utility(seed_cohort, replica)
#> # A tibble: 9 × 5
#> variable type statistic value flag
#> <chr> <chr> <chr> <dbl> <lgl>
#> 1 age numeric std_mean_diff 0.0262 FALSE
#> 2 age numeric ks 0.15 TRUE
#> 3 sex categorical total_variation 0.0875 FALSE
#> 4 life_points numeric std_mean_diff 0.183 TRUE
#> 5 life_points numeric ks 0.0875 FALSE
#> 6 ventilated categorical total_variation 0.0125 FALSE
#> 7 injury_region categorical total_variation 0.1 TRUE
#> 8 triage categorical total_variation 0.0625 FALSE
#> 9 therapy categorical total_variation 0.05 FALSE