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Table 2 Simulation results using sparse mCIA are shown. Sensitivity (Sens), Specificity (Spec), and Matthew’s correlation coefficient (MCC) for feature selection performance and Angle for estimation performance are calculated. 5-fold cross validation is used to choose the best tuning parameter combination in each method. Values within parenthesis are standard errors

From: Sparse multiple co-Inertia analysis with application to integrative analysis of multi -Omics data

sparse multiple CIAmCIA
 a1a2a3a1a2a3
scenSensSpecMCCAngleSensSpecMCCAngleSensSpecMCCAngleAngleAngleAngle
10.6750.9910.7540.8850.740.9910.8030.9010.770.9910.820.9050.8820.8470.830
 (0.285)(0.018)(0.161)(0.081)(0.205)(0.014)(0.102)(0.052)(0.155)(0.012)(0.071)(0.037)(0.025)(0.028)(0.025)
20.7540.9740.7810.9010.7590.9660.7620.8860.7550.960.7430.8750.8790.8470.833
 (0.130)(0.032)(0.058)(0.028)(0.089)(0.027)(0.046)(0.024)(0.071)(0.022)(0.041)(0.021)(0.024)(0.027)(0.023)
30.7110.9960.7940.9040.7760.9960.8460.9240.8130.9960.870.9330.9330.9150.897
 (0.316)(0.012)(0.200)(0.095)(0.231)(0.009)(0.134)(0.066)(0.177)(0.007)(0.096)(0.047)(0.011)(0.011)(0.015)
40.8260.9820.8480.9370.8460.9810.8570.9360.8450.9770.8450.9280.9330.9150.897
 (0.145)(0.029)(0.069)(0.033)(0.100)(0.022)(0.040)(0.020)(0.077)(0.020)(0.040)(0.018)(0.011)(0.011)(0.015)
50.7710.9860.8160.9080.7630.9890.8120.9020.7640.9910.8190.9030.8820.8470.83
 (0.162)(0.020)(0.079)(0.042)(0.159)(0.015)(0.077)(0.040)(0.157)(0.012)(0.074)(0.039)(0.024)(0.028)(0.025)
60.8120.930.7570.8970.7830.9440.7420.8790.7670.9540.7380.8710.8830.850.825
 (0.081)(0.042)(0.046)(0.023)(0.078)(0.031)(0.049)(0.023)(0.078)(0.024)(0.051)(0.027)(0.023)(0.025)(0.03)
70.8390.990.8730.9410.8360.9930.8750.9380.8370.9940.8780.9390.9330.9120.9
 (0.161)(0.017)(0.087)(0.043)(0.159)(0.013)(0.083)(0.041)(0.160)(0.010)(0.082)(0.042)(0.011)(0.014)(0.013)
80.880.9590.8510.9420.8650.9680.8470.9330.8630.9750.8540.9330.9330.9130.899
 (0.077)(0.039)(0.044)(0.017)(0.076)(0.026)(0.040)(0.017)(0.071)(0.021)(0.036)(0.015)(0.011)(0.014)(0.013)