Table 4.

Simulation results for the SNP approach based on 1000 Monte Carlo data sets when the true model is the AFT model with baseline density f₀(t) and multiple covariates under right censoring. Entries are as in Table 1. The True β column gives the true values of the elements of β. Entries with an asterisk (*) at the sample size indicate results for the first 300 Monte Carlo data sets, for which both delta method and nonparametric bootstrap standard errors were used, where SE_boot and CP_boot denote the average of bootstrap standard error and Monte Carlo coverage probability expressed as a percent, of 95% Wald confidence intervals using the bootstrap standard errors, respectively. For each scenario, N_K and E_K, K = 0, 1, 2, indicate the number of times the configuration of normal (N) or exponential (E) base density with the indicated K was chosen by HQ.

f₀(t)	n	Cens. rate	True β	Mean	SD	SE	CP	SE_boot	CP_boot
lognormal	200	25%	2.5	2.51	0.27	0.26	94.8
			0.5	0.49	0.15	0.15	93.5
			−0.8	−0.81	0.30	0.29	94.6
	(N₀ = 853, N₁ = 64, N₂ = 19, E₀ = 8, E₁ = 38, E₂ = 18)
gamma	200	25%	2.5	2.50	0.16	0.11	93.3
			0.5	0.50	0.06	0.06	92.3
			−0.8	−0.80	0.12	0.11	92.1
	(N₀ = 50, N₁ = 16, N₂ = 60, E₀ = 594, E₁ = 237, E₂ = 43)
	200*	25%	2.5	2.50	0.11	0.11	93.3	0.13	96.0
			0.5	0.51	0.07	0.06	92.7	0.07	95.0
			−0.8	−0.79	0.12	0.11	91.3	0.13	96.3
	500	25%	2.5	2.50	0.07	0.07	93.7
			0.5	0.50	0.04	0.04	93.1
			−0.8	−0.80	0.07	0.07	93.8
	(N₀ = 0, N₁ = 3, N₂ = 68, E₀ = 418, E₁ = 464, E₂ = 47)
log-mixture	200	25%	2.5	2.49	0.10	0.09	94.1
			0.5	0.50	0.06	0.05	92.8
			−0.8	−0.80	0.11	0.10	91.8
	(N₀ = 0, N₁ = 197, N₂ = 803, E₀ = 0, E₁ = 0, E₂ = 0)
	200*	25%	2.5	2.49	0.09	0.09	95.3	0.10	96.7
			0.5	0.50	0.06	0.05	93.0	0.06	94.0
			−0.8	−0.80	0.11	0.10	91.7	0.11	93.0
	500	25%	2.5	2.49	0.06	0.06	94.7
			0.5	0.50	0.03	0.03	94.7
			−0.8	−0.80	0.07	0.06	94.5
	(N₀ = 0, N₁ = 16, N₂ = 984, E₀ = 0, E₁ = 0, E₂ = 0)