DOandEO

#We evaluate the Accuracy, Balanced Accuracy and bias using measures such as demographic parity difference (DP) and equalized odds (EO) 
#for grouping variables such as Gender and Ethnicity.

```{r, eval=FALSE}
#This is a helper function to compute subgroup measures of any desired grouping variable
get_subgroup_measures <- function(y_true, y_pred, groups) {
  df <- data.frame(matrix(ncol=7,nrow=0, 
      dimnames=list(NULL, c("Group", "TPR", "FPR", "TNR", "FNR", "PR", "BA"))))
  sg <- unique(groups)
  for (s in sg) {
    cm <- as.matrix(table(Actual=y_true[groups == s], 
                          Predicted=y_pred[groups == s]))
    # if (dim(cm)[1] != 2 || dim(cm)[2] != 2) {
    #   next
    # }
    tpr <- cm[2,2] / (cm[2,2]+cm[2,1])
    fpr <- cm[1,2] / (cm[1,2]+cm[1,1])
    tnr <- 1 - fpr
    fnr <- 1 - tpr
    pr <- (cm[1,2]+cm[2,2]) / sum(cm)
    ba <- (tpr + tnr) / 2
    df <- rbind(df, list(Group=s, TPR=tpr, FPR=fpr, 
                         TNR=tnr, FNR=fnr, PR=pr, BA=ba))
  }
  
  df
}
# return demographic parity difference which is the 
# maximum difference in predicted positive rates between two subgroups
demographic_parity_difference <- function(sg_measures) {
  combos <- combn(sg_measures$Group, 2)
  dpd <- c()
  for (i in 1:ncol(combos)) {
    g1 <- combos[1,i]
    g1_pr <- sg_measures[sg_measures["Group"] == g1, "PR"]
    g2 <- combos[2,i]
    g2_pr <- sg_measures[sg_measures["Group"] == g2, "PR"]
    dpd <- c(dpd, abs(g1_pr - g2_pr))
  }
  max(dpd)
}
# return the equalized odds difference which is 
# the maximum difference between true positive rates or true negative rates 
# between two subgroups
equalized_odds_difference <- function(sg_measures) {
  combos <- combn(sg_measures$Group, 2)
  eod <- c()
  for (i in 1:ncol(combos)) {
    g1 <- combos[1,i]
    g1_tpr <- sg_measures[sg_measures["Group"] == g1, "TPR"]
    g1_fpr <- sg_measures[sg_measures["Group"] == g1, "FPR"]
    g2 <- combos[2,i]
    g2_tpr <- sg_measures[sg_measures["Group"] == g2, "TPR"]
    g2_fpr <- sg_measures[sg_measures["Group"] == g2, "FPR"]
    eod <- c(eod, abs(g1_tpr - g2_tpr))
    eod <- c(eod, abs(g1_fpr - g2_fpr))
  }
  max(eod)
}
```