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Table 1 Type 1 error and power of data sets of simulation 1

From: Principal-component-based multivariate regression for genetic association studies of metabolic syndrome components

Effect (b)

PCBMR

Single-Trait Association

 

GEN

ADD

DOM

REC

GEN

ADD

DOM

REC

0

5.1

4.5

5.3

5.6

5.7(2.8)

5.8(3.0)

6.1(2.9)

4.9(3.0)

0.1

5.8

5.4

6.2

4.7

5.6(3.1)

5.8(3.3)

5.9(3.0)

5.3(2.8)

0.2

10.8*

12

11.2

6.8

8.9(4.8)

10.9(6.1)

10.9(5.7)

6.4(3.4)

0.3

14.1*

18.8*

18.3*

9.1*

12.2(8.6)

14.4(9.2)

14.6(9.6)

7.3(4.4)

0.4

21.4*

26.8*

25.2*

11.3

15.9(10.0)

20.5(14.5)

19.9(13.1)

10.4(6.3)

0.5

31.9*

41.9*

36.7*

15.7*

24.3(14.8)

29.1(20.3)

27.3(18.1)

13.6(8.7)

0.6

45.4*

54.9*

50.1*

21.3*

31.6(23.2)

39.9(30.0)

36.1(26.7)

17.2(10.8)

0.7

60.3*

71.4*

65.0*

26.5*

41.9(31.3)

50.5(40.1)

47.2(36.9)

21.6(14.1)

0.8

71.9*

81.9*

77.3*

30.9*

53.3(43.6)

63.6(51.9)

58.2(46.9)

24.2(18.0)

0.9

81.7*

90.8*

84.3*

41.7*

62.5(50.4)

72.7(62.2)

66.1(55.6)

30.4(21.5)

1

91.4*

95.2*

92.8*

48.9*

72.8(62.8)

82.0(73.4)

76.7(67.3)

36.7(27.0)

  1. (The values outside the parentheses are the power (b > 0) or type I error (b = 0) of the single-trait association test without multiple-test adjustment (SATN) and the values inside the parentheses are the power (b > 0) or type I error (b = 0) of the single-trait association test with Bonferroni adjustment (SATB). * indicates that the power of PCBMR is significantly better than that of SATN; GEN: general model without assumption of genetic inheritance; ADD: additive effect model; DOM: dominant model and REC: recessive model)