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Table 2 Sensitivities, specificities, and accuracies of the classical and projection quantile methods for the simulated data from multiple experiments

From: Outlier Detection using Projection Quantile Regression for Mass Spectrometry Data with Low Replication

   Simulated Under
n Method Constant Linear Nonlinear Nonparametric
  Classical     
   Dixon (10.5, 94.9, 90.7) (17.3, 94.9, 91.0) (18.5, 94.9, 91.1) (17.7, 94.9, 91.0)
   Grubbs (20.8, 89.9, 86.5) (30.1, 89.9, 87.0) (34.4, 89.9, 87.2) (33.7, 90.0, 87.2)
  Projection Quantile     
3  Constant (90.6, 99.5, 99.0) (56.0, 98.5, 96.4) (58.8, 95.7, 93.9) (57.9, 95.7, 93.8)
   Linear (90.4, 99.5, 99.0) (84.0, 99.3, 98.5) (85.1, 96.5, 95.9) (84.8, 96.6, 96.0)
   Nonlinear (90.4, 99.5, 99.0) (84.0, 99.3, 98.5) (84.8, 98.5, 97.8) (83.5, 98.4, 97.7)
   Nonparametric (85.3, 99.2, 98.5) (82.0, 99.1, 98.2) (83.5, 99.0, 98.2) (83.2, 99.0, 98.2)
  Classical     
   Dixon (29.7, 95.0, 91.7) (44.1, 95.0, 92.4) (54.9, 94.9, 92.9) (54.5, 94.9, 92.9)
   Grubbs (49.6, 90.0, 88.0) (61.1, 90.0, 88.6) (71.2, 90.0, 89.1) (70.2, 89.9, 89.0)
  Projection Quantile     
4  Constant (89.4, 99.6, 99.1) (46.4, 99.1, 96.5) (44.3, 97.2, 94.6) (43.8, 97.3, 94.6)
   Linear (89.3, 99.6, 99.0) (86.8, 99.5, 98.8) (86.3, 97.0, 96.5) (86.4, 97.2, 96.6)
   Nonlinear (89.3, 99.6, 99.0) (86.8, 99.5, 98.8) (87.5, 99.2, 98.6) (87.8, 99.1, 98.5)
   Nonparametric (84.8, 99.3, 98.6) (84.5, 99.3, 98.5) (86.5, 99.2, 98.5) (85.9, 99.1, 98.4)
  Classical     
   Dixon (51.5, 94.6, 92.4) (63.0, 94.6, 93.0) (73.0, 94.6, 93.5) (72.6, 94.6, 93.5)
   Grubbs (70.7, 90.0, 89.0) (77.0, 90.0, 89.4) (82.3, 90.0, 89.6) (82.0, 90.1, 89.7)
  Projection Quantile     
5  Constant (89.2, 99.6, 99.1) (40.0, 99.5, 96.5) (35.9, 97.9, 94.8) (35.0, 97.9, 94.8)
   Linear (89.0, 99.6, 99.1) (87.3, 99.5, 98.9) (85.5, 97.5, 96.9) (84.6, 97.6, 96.9)
   Nonlinear (89.0, 99.6, 99.1) (87.3, 99.5, 98.9) (87.2, 99.3, 98.7) (86.2, 99.2, 98.6)
   Nonparametric (84.1, 99.4, 98.6) (84.2, 99.3, 98.5) (86.9, 99.0, 98.4) (86.0, 99.0, 98.4)
  Classical     
   Dixon (66.0, 94.4, 92.9) (73.3, 94.4, 93.3) (79.6, 94.4, 93.6) (79.9, 94.5, 93.8)
   Grubbs (81.1, 90.0, 89.6) (82.9, 90.0, 89.7) (86.1, 90.0, 89.8) (86.0, 90.2, 90.0)
  Projection Quantile     
6  Constant (87.6, 99.6, 99.0) (34.1, 99.6, 96.4) (29.7, 98.2, 94.8) (29.7, 98.4, 94.9)
   Linear (87.4, 99.6, 99.0) (85.9, 99.5, 98.8) (82.5, 97.9, 97.1) (82.7, 98.0, 97.2)
   Nonlinear (87.4, 99.6, 99.0) (85.9, 99.5, 98.8) (85.7, 99.3, 98.1) (85.0, 99.2, 98.5)
   Nonparametric (82.8, 99.3, 98.5) (83.4, 99.3, 98.5) (86.0, 99.2, 98.6) (85.8, 99.1, 98.5)
  Classical     
   Dixon (73.2, 94.3, 93.2) (78.4, 94.3, 93.5) (83.5, 94.3, 93.7) (83.6, 94.3, 93.8)
   Grubbs (85.8, 90.0, 89.8) (86.5, 90.1, 89.9) (88.2, 90.1, 90.0) (88.0, 90.2, 90.0)
  Projection Quantile     
7  Constant (86.2, 99.6, 99.0) (30.2, 99.8, 96.3) (26.3, 98.6, 95.0) (26.1, 98.6, 95.0)
   Linear (85.8, 99.6, 98.9) (85.6, 99.5, 98.8) (81.4, 98.3, 97.5) (80.4, 98.3, 97.4)
   Nonlinear (85.8, 99.6, 98.9) (85.6, 99.4, 98.7) (85.9, 99.5, 98.8) (84.7, 99.3, 98.6)
   Nonparametric (80.8, 99.3, 98.4) (82.3, 99.3, 98.5) (86.2, 99.2, 98.6) (85.8, 99.2, 98.5)
  Classical     
   Dixon (71.2, 94.5, 93.4) (76.7, 94.5, 93.6) (82.4, 94.5, 93.9) (82.7, 94.5, 93.9)
   Grubbs (89.1, 90.0, 90.0) (87.7, 90.0, 89.9) (89.2, 90.0, 90.0) (89.3, 90.0, 89.9)
  Projection Quantile     
8  Constant (85.9, 99.7, 99.0) (26.5, 99.8, 96.1) (23.2, 98.0, 94.2) (24.1, 97.9, 94.2)
   Linear (85.7, 99.6, 98.9) (84.8, 99.4, 98.7) (77.1, 98.1, 97.0) (77.3, 98.1, 97.1)
   Nonlin (85.7, 99.6, 98.9) (84.8, 98.8, 98.1) (84.4, 99.4, 98.7) (84.0, 99.3, 98.5)
   Nonparametric (80.2, 99.4, 98.4) (81.6, 99.3, 98.4) (85.7, 99.2, 98.5) (86.2, 99.1, 98.5)