เปรียบเทียบวิธี

	การวิเคราะห์ ROC (Receiver Operating Characteristic)	การวิเคราะห์จำแนก (Discriminant Analysis)
สาขาวิชา	สถิติศาสตร์	สถิติศาสตร์
ตระกูล	Hypothesis test	Latent structure
ปีกำเนิด	1954 (signal detection); 1982 (AUC formalization)	1936
ผู้ริเริ่ม	Peterson, Birdsall & Fox (signal detection theory); Hanley & McNeil (medical statistics)	Ronald A. Fisher
ประเภท	Diagnostic accuracy evaluation	Supervised classification and dimension reduction
แหล่งต้นตำรับ	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.
ชื่อเรียกอื่น	ROC curve analysis, AUC analysis, sensitivity-specificity analysis, diagnostic accuracy analysis	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
ที่เกี่ยวข้อง	4	4
สรุป	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.