Table 3

FDRS design for equi-correlated data
m = 1000 m = 10000 m = 100000
α1 π0 Δ = 1 Δ = 1.6 Δ = 1 Δ = 1.6 Δ = 1 Δ = 1.6
0.1 .95 2.7 (3%;) 18.1 (0%;) 20.6 (5%;) 169.9 (0%;) 180.2 (5%;) 1682.2 (0%;)
.99 0.4 (0%;) 3.2 (0%;) 2.0 (12%;) 22.7 (0%;) 16.4 (19%;) 214.4 (1%;)
0.2 .95 3.9 (9%;) 21.5 (1%;) 30.6 (12%;) 203.4 (1%;) 300.6 (14%;) 2015.9 (1%;)
.99 0.6 (7%;) 3.9 (1%;) 2.9 (26%;) 28.3 (1%;) 26.0 (33%;) 269.5 (2%;)
0.5 .95 7.3 (22%;) 26.8 (3%;) 60.5 (28%;) 257.3 (4%;) 576.0 (29%;) 2554.7 (4%;)
.99 1.1 (25%;) 4.9 (3%;) 5.7 (6%;) 37.9 (4%;) 48.8 (78%;) 363.3 (4%;)

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 (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

Open Data