Table 2.

Simulation results for the settings with p = 3 and t = 50.

ℳ1	ζ	n	ℳ2	$\mathrm{\Delta }{\widehat{c}}_s^1(SD)$	$\mathrm{\Delta }{\widehat{c}}_s^2(SD)$	$\mathrm{\Delta }{\widehat{c}}_g^1(SD)$	$\mathrm{\Delta }{\widehat{c}}_g^2(SD)$	ctrue
Cox	0.3	50	Cox	0.076(0.072)	0.020(0.049)	0.062(0.092)	0.000(0.062)	0.834
			AFT‡			0.069(0.075)	0.003(0.050)
		500	Cox	0.068(0.020)	0.027(0.014)	0.040(0.040)	0.003(0.015)
			AFT‡			0.054(0.019)	0.011(0.013)
	0.6	50	Cox	0.035(0.042)	0.010(0.035)	0.023(0.045)	0.001(0.034)	0.830
			AFT‡			0.029(0.042)	0.002(0.034)
		500	Cox	0.031(0.012)	0.013(0.010)	0.010(0.016)	0.001(0.010)
			AFT‡			0.020(0.012)	0.000(0.010)
AFT†	0.3	50	Cox	0.076(0.072)	0.020(0.049)	0.063(0.092)	0.000(0.061)	0.834
			AFT‡			0.069(0.076)	0.003(0.050)
		500	Cox	0.068(0.020)	0.027(0.014)	0.041(0.040)	0.003(0.027)
			AFT‡			0.055(0.020)	0.010(0.009)
	0.6	50	Cox	0.035(0.042)	0.010(0.034)	0.024(0.046)	0.001(0.034)	0.830
			AFT‡			0.029(0.042)	0.002(0.033)
		500	Cox	0.031(0.012)	0.013(0.011)	0.010(0.016)	0.001(0.010)
			AFT‡			0.020(0.012)	0.000(0.010)

Note that both true underlying models for survival time and censoring time are Cox PH models; $\mathrm{\Delta }{\widehat{c}}_s^1(SD)$ and $\mathrm{\Delta }{\widehat{c}}_s^2(SD)$

are the same when ℳ₂ is Cox or AFT because they do not require the estimation of censoring weights.

^†Mis-specifying the model for survival time as an AFT model with the log-logistic distribution.

^‡Mis-specifying the model for censoring time as an AFT model with the log-logistic distribution.