risk_thresholds() exposes the conservative screening thresholds used by
MOAT audit modules. These thresholds are heuristics for pre-analysis review:
they make study-design risks visible before downstream interpretation.
Value
A tibble::tibble() with columns module, metric, risk,
condition, and notes.
Examples
risk_thresholds()
#> # A tibble: 34 × 5
#> module metric risk condition notes
#> <chr> <chr> <chr> <chr> <chr>
#> 1 risk levels unknown unkn… insuffic… Unkn…
#> 2 risk levels low low no confi… Low-…
#> 3 risk levels moderate mode… visible … Mode…
#> 4 risk levels high high strong d… High…
#> 5 risk levels critical crit… non-iden… Crit…
#> 6 design categorical complete separation crit… each lev… Comp…
#> 7 design categorical Cramer's V high Cramer's… Asso…
#> 8 design categorical Cramer's V / p-value / sparse … mode… Cramer's… Spar…
#> 9 design continuous standardized mean difference high standard… Cont…
#> 10 design continuous standardized mean difference / … mode… standard… Visi…
#> # ℹ 24 more rows