SummaryThe objective of the present report is to demonstrate the use of receiver-operator characteristics (ROC) analysis in the selection of diagnostic tests for iron deficiency in a specific population. Conventional ROC curves were prepared with true positive fraction (TPF) and false positive fraction (FPF) determined by the application of different cut-off points for four indicators of iron status. ROC plots were then transformed into normal deviate scales. The advantages of Gaussian transformation of TPF and FPF when underlying decision functions are normally distributed are: (i) the ROC curve is a straight line; and (ii) the separation between the two distributions and shape of these distributions can be simply quantitated as intercepts and slopes. In the present study, pretreatment hemoglobin concentration was the most robust diagnostic indicator of iron deficiency as operationally defined by a response of hemoglobin to iron treatment. Free erythrocyte protoporphyrin was a more sensitive and specific predictor than either serum ferritin or transferin saturation when a stringent operational definition of iron deficiency was used. These findings illustrate the utility of ROC analysis in discriminating between diagnostic indicators having different degrees of accuracy.