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Table 3 Median (minimum, maximum) number of correctly identified non-zero and zero coefficients, N = 1000, 1000 simulated datasets

From: Least absolute shrinkage and selection operator type methods for the identification of serum biomarkers of overweight and obesity: simulation and application

Scenario

1

2

3

4

5

Type

Non-Zero

Zero

Non-Zero

Zero

Non-Zero

Zero

Non-Zero

Zero

Non-Zero

Zero

Truth

5

95

5

95

5

95

5

95

20

80

Overweight

 LASSO

3 (0,5)

91 (61,95)

3 (1,5)

92 (56,95)

5 (4,5)

81 (39,95)

4 (2,5)

89 (43,95)

13 (8,18)

74.5 (39,80)

 Adaptive LASSO

3 (0,5)

82 (54,95)

2 (1,5)

83 (50,95)

5 (4,5)

82 (51,95)

4 (2,5)

81 (48,95)

9 (4,15)

68 (41,80)

 Elastic Net

3 (0,5)

86 (0,95)

3 (1,5)

88 (0,95)

5 (4,5)

77 (38,95)

4 (2,5)

86 (34,95)

16 (9,20)

67 (0,80)

 Iterated LASSO

2 (0,5)

91 (57,95)

2 (1,5)

93 (64,95)

5 (4,5)

82 (54,95)

3 (2,5)

90 (57,95)

11 (5,16)

76 (50,80)

 Bootstrap-Enhanced LASSO-75

3 (0,5)

86 (70,95)

2 (0,4)

86 (72,95)

5 (4,5)

82 (62,93)

4 (2,5)

81 (60,94)

12 (7,16)

72 (54,80)

 Weighted Fusion

4 (0,5)

72 (1,95)

5 (1,5)

72 (0,95)

5 (4,5)

77 (24,90)

4 (2,5)

77 (26,89)

20 (9,20)

65 (0,74)

Obese

 LASSO

5 (3,5)

82 (49,95)

3 (2,5)

91 (41,95)

5 (5,5)

74 (44,92)

4 (3,5)

83 (42,95)

19 (14,20)

61 (37,78)

 Adaptive LASSO

5 (3,5)

82.5 (50,95)

4 (1,5)

82 (53,95)

5 (5,5)

82 (43,95)

5 (3,5)

81 (53,95)

15 (10,20)

60 (38,79)

 Elastic Net

5 (4,5)

79 (26,94)

4 (2,5)

88 (25,95)

5 (5,5)

71 (24,94)

4 (3,5)

80 (23,95)

19 (15,20)

52 (0,75)

 Iterated LASSO

5 (3,5)

84 (60,95)

3 (1,5)

91 (56,95)

5 (5,5)

80 (60,95)

4 (3,5)

86 (62,95)

16 (12,20)

72 (56,80)

 Bootstrap-Enhanced LASSO-75

5 (3,5)

83 (63,95)

3 (1,5)

84 (64,95)

5 (5,5)

80 (61,93)

4 (2,5)

83 (66,94)

16 (10,20)

73 (62,80)

 Weighted Fusion

5 (3,5)

88 (32,94)

3 (2,5)

89 (1,95)

5 (5,5)

57 (39,95)

4 (3,5)

64 (46,95)

20 (14,20)

61 (1,76)