Table 4

FNS design for equi-correlated data
m = 1000 m = 10000 m = 100000
m2 π0 Δ = 1 Δ = 1.6 Δ = 1 Δ = 1.6 Δ = 1 Δ = 1.6
0.01m .95 8.0 (13%;) 15.2 (53%;) 77.3 (13%;) 141.2 (43%;) 768.0 (13%;) 1392.8 (41%;)
.99 2.4 (0%;) 5.6 (1%;) 17.7 (0%;) 48.6 (1%;) 168.5 (0%;) 471.5 (1%;)
0.05m .95 14.4 (12%;) 28.5 (4%;) 135.4 (13%;) 278.9 (4%;) 1342.9 (13%;) 2783.1 (4%;)
.99 3.0 (15%;) 6.3 (3%;) 21.6 (21%;) 55.3 (4%;) 207.9 (21%;) 537.4 (5%;)
0.1m .95 15.8 (21%;) 30.6 (5%;) 149.0 (22%;) 299.7 (5%;) 1473.5 (22%;) 2990.8 (5%;)
.99 3.2 (28%;) 6.4 (5%;) 22.8 (39%;) 57.1 (8%;) 216.4 (41%;) 556.2 (8%;)

The mean number of rejected alternatives for the integrated design and the improvement in percent compared to the pilot design (in parentheses) with α = 0.05, n1 = 6, n2 = 12, ρ = 0.5, ms = 6 (20000 simulation runs per scenario for m = 1000, m = 10000; 10000 simulation runs for m = 100000).

Zehetmayer and Posch

Zehetmayer and Posch BMC Bioinformatics 2012 13:81   doi:10.1186/1471-2105-13-81

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