Table 2.

Pros and Cons of the Nonparametric (Empirical) and Parametric Receiver Operating Characteristic Curve Approaches

	Nonparametric ROC curve	Parametric ROC curve
Pros	No need for assumptions about the distribution of data.	Shows a smooth curve.
	Provides unbiased estimates of sensitivity and specificity.	Compares plots at any sensitivity and specificity value.
	The plot passes through all points.
	Uses all data.
	Computation is simple.
Cons	Has a jagged or staircase appearance.	Actual data are discarded.
	Compares plots only at observed values of sensitivity or specificity.	Curve does not necessarily go through actual points.
		ROC curves and the AUC are possibly biased.
		Computation is complex.

ROC: receiver operating characteristic curve, AUC: area under the curve.