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Table 1 Mean (SD) of \( {R}_{BS}^2(2) \) for the training sets over 300 simulations

From: Combined performance of screening and variable selection methods in ultra-high dimensional data in predicting time-to-event outcomes

Selection approach

Weak signal

Strong signal

n = 150

n = 300

n = 150

n = 300

ISIS-LASSO

0.122 (0.109)

0.578 (0.071)

0.335 (0.318)

0.797 (0.071)

ISIS-ALASSO

0.108 (0.108)

0.578 (0.071)

0.337 (0.322)

0.797 (0.071)

ISIS-RSF

0.069 (0.088)

0.564 (0.105)

0.232 (0.284)

0.790 (0.086)

SIS

0.065 (0.085)

0.303 (0.116)

0.114 (0.119)

0.491 (0.177)

SIS-LASSO

0.112 (0.093)

0.306 (0.113)

0.142 (0.119)

0.491 (0.177)

SIS-ALASSO

0.093 (0.092)

0.306 (0.113)

0.137 (0.120)

0.491 (0.177)

SIS-RSF

0.063 (0.082)

0.294 (0.125)

0.097 (0.104)

0.482 (0.178)

PSIS

0.756 (0.116)

0.811 (0.038)

0.642 (0.183)

0.869 (0.047)

PSIS-LASSO

0.875 (0.051)

0.805 (0.037)

0.869 (0.062)

0.874 (0.049)

PSIS-ALASSO

0.874 (0.052)

0.780 (0.042)

0.869 (0.063)

0.849 (0.057)

PSIS-RSF

0.688 (0.088)

0.413 (0.109)

0.655 (0.111)

0.555 (0.167)

LASSO

0.758 (0.138)

0.834 (0.043)

0.787 (0.136)

− 0.211 (0.036)

ALASSO

0.583 (0.115)

0.611 (0.058)

0.812 (0.095)

0.815 (0.063)

  1. SD standard deviation