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Table 2 DLBCL data: Method comparison for estimating the Δ Δ C q -value

From: Unaccounted uncertainty from qPCR efficiency estimates entails uncontrolled false positive rates

 

Estimate

se

t-value

df

p-value

LCL

UCL

mir127 vs rnu6b

       

EC

2.67

1.13

2.37

22

2.68·10−2

0.336

5.01

EC&VA1

2.67

1.13

2.37

22

2.71·10−2

0.331

5.01

EC&VA2

2.67

1.13

2.36

22

2.75·10−2

0.325

5.02

Bootstrap

2.68

1.05

  

1.00·10−3

0.876

4.82

mir127 vs rnu24

       

EC

2.38

1.08

2.2

22

3.87·10−2

0.136

4.63

EC&VA1

2.38

1.09

2.19

22

3.91·10−2

0.13

4.64

EC&VA2

2.38

1.09

2.19

22

3.94·10−2

0.126

4.64

Bootstrap

2.42

1.18

  

1.00·10−2

0.416

5.02

mir143 vs rnu6b

       

EC

1.17

0.846

1.38

22

1.82·10−1

-0.589

2.92

EC&VA1

1.17

0.846

1.38

22

1.82·10−1

-0.59

2.92

EC&VA2

1.17

0.847

1.37

22

1.83·10−1

-0.592

2.92

Bootstrap

1.15

0.794

  

1.44·10−1

-0.341

2.7

mir143 vs rnu24

       

EC

0.878

0.81

1.08

22

2.90·10−1

-0.801

2.56

EC&VA1

0.878

0.81

1.08

22

2.90·10−1

-0.802

2.56

EC&VA2

0.878

0.811

1.08

22

2.90·10−1

-0.803

2.56

Bootstrap

0.897

0.822

  

2.67·10−1

-0.603

2.58

  1. EC efficiency corrected LMM estimate ignoring the uncertainty of the efficiency estimates. EC&VA1 EC and variance adjusted LMM estimate using the delta method. EC&VA2 EC and variance adjusted LMM estimate using Monte Carlo integration. Bootstrap Estimate by the bootstrap described in Section “Inference for Δ Δ C q by the bootstrap method” fitting the LMM and using the EC estimate. Bootstrap shows the mean and standard deviation of 4 bootstrap samples using the EC estimate. The last two columns show the 95 % lower and upper confidence interval limits