Table 5.

Results from the comparative feasibility study summarizing parameter and standard error estimates across 500 datasets generated from model (4) using EM algorithm described in section 2.1. Random sampling and three ODS designs were considered, D[0, 190, 0], D[10, 180, 0] and D[25, 165, 0]. Six feasibility study scenarios were examined with pr(g_i = 1|x_o,i; ω) equal to 0.2 in CF-1 and CF-4, and 0.3 in CF-3 and CF-6, In CF-2 and CF-5 it was allowed to vary as a function of race and city according to the estimates shown in table 4. For β^(e) ≡ (β_g, β_gt) we considered the values (0, 0) and (0.35, −0.37). Standard error is the square root of the average estimated variance, and pr(Reject H₀) is the proportion of datasets in which the null hypothesis (i.e., the parameter is zero) was rejected at the two-sided α = 0.05 significance level.

	(βg, βgt)	pr(xe,i|xo,i; ω)	CFS Setting	βg				βgt
				Random Sampling	D[0,190,0]	D[10,180,0]	D[25,165,0]	Random Sampling	D[0,190,0]	D[10,180,0]	D[25,165,0]
Standard Error	(0,0)	0.2	CF-1	0.46	0.38	0.39	0.39	0.42	0.28	0.28	0.29
	(0,0)	f(race, site)	CF-2	0.40	0.33	0.34	0.34	0.36	0.24	0.24	0.25
	(0,0)	0.3	CF-3	0.40	0.32	0.34	0.34	0.36	0.24	0.24	0.25
	(0.35,−0.37)	0.2	CF-4	0.44	0.37	0.38	0.38	0.42	0.28	0.28	0.28
	(0.35,−0.37)	f(race, site)	CF-5	0.39	0.33	0.34	0.34	0.36	0.24	0.24	0.25
	(0.35,−0.37)	0.3	CF-6	0.38	0.32	0.33	0.33	0.36	0.24	0.24	0.25
pr(Reject H0)	(0,0)	0.2	CF-1	0.06	0.06	0.06	0.06	0.04	0.05	0.04	0.04
	(0,0)	f(race, site)	CF-2	0.05	0.07	0.05	0.06	0.03	0.04	0.04	0.05
	(0,0)	0.3	CF-3	0.06	0.03	0.04	0.04	0.04	0.04	0.03	0.03
	(0.35,−0.37)	0.2	CF-4	0.13	0.15	0.12	0.15	0.14	0.23	0.25	0.22
	(0.35,−0.37)	f(race, site)	CF-5	0.15	0.20	0.18	0.19	0.18	0.38	0.40	0.35
	(0.35,−0.37)	0.3	CF-6	0.15	0.17	0.18	0.17	0.16	0.34	0.34	0.30