For each group, the disparate-impact ratio is its favourable-
outcome rate divided by the privileged group's rate. A value below
0.8 is the standard legal indicator of adverse impact.
Usage
morie_fairness_disparate_impact(
y_pred,
group,
privileged = NULL,
favorable = 1
)
Arguments
- y_pred
Vector of decisions / assignments per individual.
- group
Protected-attribute vector aligned with y_pred.
- privileged
Reference group. If NULL, the highest-rate
group is inferred and a warning is emitted.
- favorable
Value of y_pred that counts as favourable
(default 1).
Value
A morie_fairness_result; headline value is the
worst (smallest) ratio across groups.
Examples
pred <- c(1, 1, 1, 1, 1, 1, 1, 1, 0, 0)
race <- c("A","A","A","A","A","B","B","B","B","B")
morie_fairness_disparate_impact(pred, race, privileged = "A")$value
#> [1] 0.6
