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Table 1 Information of each simulated dataset

From: A comparative study of forest methods for time-to-event data: variable selection and predictive performance

model form covariate
A1 1.5x1i + Ι(x5i = 2) x1i − x2i~U(0, 1), x3i − x4i~Ν(0, 1),
x5i − x6i~DiscreteU(1, 2), x7i − x8i~DiscreteU(1, 4),
x9i − x10i~DiscreteU(1, 8)a
A2 1.5x1i + Ι(x7i ≥ 3)
A3 1.5x1i + Ι(x9i ≥ 5)
B1 Ι(x1i > 0.5)  Ι(x5i = 2)
B2 Ι(x1i > 0.5)  Ι(x7i ≥ 3)
B3 Ι(x1i > 0.5)  Ι(x9i ≥ 5)
C x1i + 1.5x2i x1i − x10i~MVΝ(0, Σ)b
D1 2x1i + 3x2i x1i − xMi~Ν(0, 1)c
D2 2x1i + 3x2i x1i − xMi~DiscreteU(1, 2)a
  1. a DiscreteU(1, k) is the discrete uniform distribution, a simple distribution that puts equal weight on the integers from 1 to k
  2. b Σ is a squared matrix with all diagonal elements equal to 1 and all off-diagonal elements equal to ρ
  3. c M is the number of covariates