Table 1

Accuracies of scoring criteria

Scoring Criterion

200

400

800

1600

Total


1

scoreα = 15

4379

5426

6105

6614

22524


2

scoreα = 12

4438

5421

6070

6590

22519


3

scoreα = 18

4227

5389

6095

6625

22336


4

scoreα = 9

4419

5349

5996

6546

22313


5

scoreα = 21

3989

5286

6060

6602

21934


6

scoreα = 6

4220

5165

5874

6442

21701


7

scoreMML1

4049

5111

5881

6463

21504


8

scoreα = 24

3749

5156

5991

6562

21448


9

scoreMDR

4112

4954

5555

5982

20603


10

scoreα = 3

3839

4814

5629

6277

20559


11

scoreEpi2

3571

4791

5648

6297

20307


12

scoreα = 30

3285

4779

5755

6415

20234


13

scoreMML2

3768

4914

5754

5780

20216


14

scoreEpi1

2344

5225

6065

6553

20187


15

scoreSuz1

3489

4580

5521

6215

19805


16

scoreα = 36

2810

4393

5464

6150

18817


17

scoreα = 42

2310

4052

5158

5895

17415


18

scoreK2

1850

3475

5095

6116

16536


19

scoreSuz2

2245

3529

4684

5673

16131


20

scoreα = 54

1651

3297

4492

5329

14769


21

scoreAIC2

3364

3153

2812

2520

11847


22

scoreAIC1

2497

1967

1462

1126

7052


23

scoreα = 162

26

476

1300

2046

3848


The number of times out of 7000 data sets that each scoring criterion identified the correct model for sample sizes of 200, 400, 800, and 1600. The last column gives the total accuracy over all sample sizes. The scoring criteria are listed in descending order of total accuracy.

Jiang et al. BMC Bioinformatics 2011 12:89   doi:10.1186/1471-2105-12-89

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