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Table 1 Results of the simulation study.

From: Incorporating pathway information into boosting estimation of high-dimensional risk prediction models

Model

intercept

Lasso

Li&Li

lik.boost

PathBoost

1

762.5 (14.4)

83.6 (2.6)

42.5 (1.1)

83.4 (2.4)

61.0 (1.7)

2

305.8 (5.1)

91.0 (2.7)

80.8 (1.9)

89.7 (2.7)

64.8 (1.8)

3

215.6 (4.1)

32.6 (0.9)

24.9 (0.8)

32.1 (0.9)

26.5 (0.7)

4

131.1 (2.4)

32.6 (0.9)

29.9 (0.7)

32.5 (0.9)

26.9 (0.7)

5

525.7 (9.9)

87.9 (2.6)

61.6 (1.5)

85.6 (2.2)

62.2 (1.6)

6

171.6 (3.3)

32.9 (0.9)

27.6 (0.7)

32.2 (0.9)

26.9 (0.8)

  1. Predictive mean squared error, mean and standard errors (in parentheses), for an intercept-only model, the Lasso, the pathway-based procedure proposed in [9] (Li&Li), componentwise likelihood-based boosting (lik.boost), and boosting with pathway information (PathBoost) for six types of generating models.