[Use of ROC analysis in psychiatry]

The fundamental principles of ROC analysis are described. This method provides a means to assess the overall discriminant power of psychiatric rating scales for the full range of their scores. For each cut-off, an instrument has a sensitivity (true positive rate) and a specificity (true negative rate). High values of these coefficients are desirable although they are inversely related. ROC curves can be obtained by plotting the false positive rate and the true positive rate for different thresholds of the rating scale. The curves which would be obtained with a perfect, a worthless and a typical instrument are drawn to illustrate various situations found in ROC analysis. Among the several indices proposed, the area under the curve (AUC) is the most commonly used index to assess the overall discriminant power of an instrument. To calculate this area, the non parametric trapezoidal method is advocated. The area under the curve varies between 0.50 which corresponds to the chance line up to 1.0, a value associated with perfect accuracy. This parameter can be interpreted as the probability of classifying correctly the subjects of a pair where one is normal and one is diseased. Then, the appropriate statistic to compare several ROC indices is provided for the general case of independent observations. When the observations are paired, the standard error of the difference between two areas needs to be corrected.(ABSTRACT TRUNCATED AT 250 WORDS)