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Table 3 FDRS design for equi-correlated data

From: False discovery rate control in two-stage designs

  

m= 1000

m= 10000

m= 100000

α 1

π 0

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%;)

  1. 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).
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BMC Bioinformatics

ISSN: 1471-2105

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