There is currently no consensus on the most biologically meaningful way to calculate discrete-individual repeatability of stress response curves. In the current study, we compared three metrics of discrete-individual repeatability that incorporate the whole stress response curve: profile repeatability, Kullback-Leibler (KL) divergence, and hypothalamic-pituitary-adrenal (HPA) flexibility. As part of this work, we present a new R package for computing profile repeatability, "profrep." Using three datasets (one synthetic and two corticosterone datasets from live birds), our objectives were (1) to compare how these metrics correlate with one another and (2) to determine how representative repeatability scores of fewer replicates were to the "consensus" score (i.e., the score of the full dataset). We found that (1) these three discrete-individual repeatability metrics do not consistently correlate with one another
(2) KL divergence and HPA flexibility are poor at distinguishing individuals from each other (i.e., they give similar scores for each individual regardless of perceived repeatability)
and (3) profile repeatability tends to overestimate repeatability when fewer replicates are available, and the consensus score is low. Despite this drawback of profile repeatability, we suggest that it may be the most well-suited metric for assessing discrete-individual repeatability.