Table 2 An overview of regression models and key performance measures
From: Evaluation of absolute quantitation by nonlinear regression in probe-based real-time PCR
Regression Model | Results | |||||||
|---|---|---|---|---|---|---|---|---|
Backgr. Corr. | Log10 transform | Weight | Baseline drift corr. | Bad fits | Mean R2 | Intra-assay variation | Numerical Bias | |
1 | No | No | No | No | No | 0.9987 | 58 % | 89 % |
2 | No | No | No | Yes | No | 0.9988 | 83 % | 102 % |
3 | No | No | ← | Yes | No | 0.9982 | 80 % | 121 % |
4 | No | Yes | No | No | No | 0.9987 | 59 % | 85 % |
5 | No | Yes | No | Yes | No | 0.9991 | 94 % | 97 % |
6 | No | Yes | ← | Yes | Yes | 0.9986 | 104 % | 130 % |
7 | No | Yes | → | Yes | No | 0.9985 | 101 % | 115 % |
8 | Yes | No | ← | No | No | 0.9978 | 94 % | 166 % |
9 | Yes | Yes | → | No | Yes | 0.9768 | 29963 % | 340 % |
10 | Yes | No | No | No | No | 0.9922 | 83 % | 102 % |
11 | Yes | Yes | No | No | Yes | 0.9607 | 36336 % | 526 % |
CT | Yes | 24 % | ||||||