Compara mètodes

	Anàlisi ROC (Característica Operativa del Receptor)	Anàlisi discriminant
Camp	Estadística	Estadística
Família	Hypothesis test	Latent structure
Any d'origen	1954 (signal detection); 1982 (AUC formalization)	1936
Autor original	Peterson, Birdsall & Fox (signal detection theory); Hanley & McNeil (medical statistics)	Ronald A. Fisher
Tipus	Diagnostic accuracy evaluation	Supervised classification and dimension reduction
Font seminal	Hanley, J. A., & McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143(1), 29–36.	Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.
Àlies	ROC curve analysis, AUC analysis, sensitivity-specificity analysis, diagnostic accuracy analysis	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
Relacionats	4	4
Resum	ROC analysis evaluates how well a continuous or ordinal test variable discriminates between two binary outcome classes. By plotting the true positive rate (sensitivity) against the false positive rate (1 − specificity) across all decision thresholds, it produces a curve whose area under the curve (AUC) quantifies overall discriminative power, ranging from 0.5 (chance) to 1.0 (perfect discrimination).	Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error.