Current data
For R1, R2 and R2* and under field strenth 1.5T and 3.0T, we compare F-Saline vs S-Saline and F-Blood vs S-Blood.
Saline
First compare F-Saline vs S-Saline under linear models. Chi-square tests with 2 degrees of freedom (intercept + slope) are used to compare the two regression lines.
The above results show that F-Saline vs S-Saline are significantly different for R1 under 3.0T and R2* under 1.5T.
Blood
Then we consider F-Blood vs S-Blood under quadratic models. Chi-square tests with 3 degrees of freedom (intercept + linear + quadratic terms) are used to compare the two regression lines.
The above results show that F-Blood vs S-Blood are significantly different for R1 under 3.0T and R2* under both 1.5T and 3.0T.
Regression coefficients for saline and blood
| Var | FS | type | b0 | b1 |
|---|---|---|---|---|
| R1 | 1.5 | Saline (S) | 0.87 (-0.32, 2.05) | 15.48 (14.58, 16.37) |
| R1 | 1.5 | Saline (A) | 0.75 (-0.02, 1.53) | 16.64 (16.05, 17.23) |
| R1 | 3.0 | Saline (S) | 0.65 (0.35, 0.96) | 8.6 (8.37, 8.83) |
| R1 | 3.0 | Saline (A) | 0.52 (-0.13, 1.17) | 9.35 (8.86, 9.84) |
| R2 | 1.5 | Saline (S) | 4.01 (-6.26, 14.29) | 58.81 (51.03, 66.59) |
| R2 | 1.5 | Saline (A) | 3.23 (1.38, 5.08) | 59.13 (57.73, 60.53) |
| R2 | 3.0 | Saline (S) | 4.73 (0.93, 8.53) | 58.88 (56.01, 61.75) |
| R2 | 3.0 | Saline (A) | -0.36 (-8.08, 7.35) | 62.01 (56.17, 67.85) |
| R2* | 1.5 | Saline (S) | 4.29 (-2.72, 11.31) | 64.93 (59.62, 70.24) |
| R2* | 1.5 | Saline (A) | 10.57 (6.13, 15.01) | 56.59 (53.23, 59.96) |
| R2* | 3.0 | Saline (S) | 4.12 (-2.9, 11.13) | 60.88 (55.57, 66.19) |
| R2* | 3.0 | Saline (A) | 3.89 (-3.16, 10.94) | 60.13 (54.8, 65.47) |
| Var | FS | type | b0 | b1 | b2 |
|---|---|---|---|---|---|
| R1 | 1.5 | Blood (S) | 0.37 (-7.18, 7.91) | 12.7 (-2.99, 28.39) | 1.02 (-5.37, 7.41) |
| R1 | 1.5 | Blood (A) | 0.63 (-5.53, 6.79) | 14.56 (1.76, 27.37) | 0.6 (-4.62, 5.82) |
| R1 | 3.0 | Blood (S) | 0.53 (-1.09, 2.16) | 5.77 (2.4, 9.15) | 1.31 (-0.06, 2.69) |
| R1 | 3.0 | Blood (A) | 0.51 (-2.27, 3.3) | 7.4 (1.61, 13.18) | 0.9 (-1.46, 3.26) |
| R2 | 1.5 | Blood (S) | 13.61 (-30.99, 58.21) | 34.42 (-58.31, 127.15) | 20.38 (-17.41, 58.17) |
| R2 | 1.5 | Blood (A) | 12.07 (-21.54, 45.68) | 43.76 (-26.12, 113.64) | 21.26 (-7.22, 49.74) |
| R2 | 3.0 | Blood (S) | 22.51 (-39.84, 84.86) | 6.77 (-122.87, 136.42) | 30.43 (-22.41, 83.27) |
| R2 | 3.0 | Blood (A) | 13.6 (-32.68, 59.88) | 45.73 (-50.49, 141.94) | 13.68 (-25.54, 52.89) |
| R2* | 1.5 | Blood (S) | 81.26 (37.57, 124.96) | 31.83 (-59.02, 122.68) | 42.08 (5.05, 79.11) |
| R2* | 1.5 | Blood (A) | 114.87 (101.75, 127.99) | -21.53 (-48.81, 5.75) | 71.94 (60.82, 83.06) |
| R2* | 3.0 | Blood (S) | 52.47 (20.81, 84.14) | 43.05 (-22.79, 108.88) | 30.38 (3.55, 57.22) |
| R2* | 3.0 | Blood (A) | 54.28 (40.38, 68.17) | 39.65 (10.77, 68.53) | 36.22 (24.45, 48) |
95% Confidence limits for regression lines
Saline
- R1-1.5T
- Saline (S) \[\begin{align} y =& 0.866 + 15.477x \pm 3.182 \sqrt{0.138 -0.178x + 0.079x^2 } \end{align}\]
- Saline (A) \[\begin{align} y =& 0.752 + 16.639x \pm 3.182 \sqrt{0.059 -0.077x + 0.034x^2 } \end{align}\]
- R1-3.0T
- Saline (S) \[\begin{align} y =& 0.653 + 8.601x \pm 3.182 \sqrt{0.009 -0.012x + 0.005x^2 } \end{align}\]
- Saline (A) \[\begin{align} y =& 0.52 + 9.348x \pm 3.182 \sqrt{0.041 -0.053x + 0.024x^2 } \end{align}\]
- R2-1.5T
- Saline (S) \[\begin{align} y =& 4.01 + 58.81x \pm 3.18 \sqrt{10.43 -13.48x + 5.97x^2 } \end{align}\]
- Saline (A) \[\begin{align} y =& 3.23 + 59.13x \pm 3.18 \sqrt{0.34 -0.44x + 0.19x^2 } \end{align}\]
- R2-3.0T
- Saline (S) \[\begin{align} y =& 4.73 + 58.88x \pm 3.18 \sqrt{1.42 -1.84x + 0.81x^2 } \end{align}\]
- Saline (A) \[\begin{align} y =& -0.36 + 62.01x \pm 3.18 \sqrt{5.88 -7.59x + 3.37x^2 } \end{align}\]
- R2*-1.5T
- Saline (S) \[\begin{align} y =& 4.29 + 64.93x \pm 3.18 \sqrt{4.86 -6.28x + 2.78x^2 } \end{align}\]
- Saline (A) \[\begin{align} y =& 10.57 + 56.59x \pm 3.18 \sqrt{1.95 -2.52x + 1.12x^2 } \end{align}\]
- R2*-3.0T
- Saline (S) \[\begin{align} y =& 4.12 + 60.88x \pm 3.18 \sqrt{4.86 -6.28x + 2.78x^2 } \end{align}\]
- Saline (A) \[\begin{align} y =& 3.89 + 60.13x \pm 3.18 \sqrt{4.9 -6.34x + 2.81x^2 } \end{align}\]
Blood
- R1-1.5T
- Blood (S) \[\begin{align} y =& 0.37 + 12.7x + 1.02x^2 \pm 4.3 \sqrt{3.07 -11.5x + 17.53x^2 -10.59x^3 + 2.21x^4} \end{align}\]
- Blood (A) \[\begin{align} y =& 0.63 + 14.56x + 0.6x^2 \pm 4.3 \sqrt{2.05 -7.66x + 11.68x^2 -7.05x^3 + 1.47x^4} \end{align}\]
- R1-3.0T
- Blood (S) \[\begin{align} y =& 0.53 + 5.77x + 1.31x^2 \pm 4.3 \sqrt{0.14 -0.53x + 0.81x^2 -0.49x^3 + 0.1x^4} \end{align}\]
- Blood (A) \[\begin{align} y =& 0.51 + 7.4x + 0.9x^2 \pm 4.3 \sqrt{0.42 -1.57x + 2.38x^2 -1.44x^3 + 0.3x^4} \end{align}\]
- R2-1.5T
- Blood (S) \[\begin{align} y =& 13.61 + 34.42x + 20.38x^2 \pm 4.3 \sqrt{107.44 -402x + 612.48x^2 -370x^3 + 77.16x^4} \end{align}\]
- Blood (A) \[\begin{align} y =& 12.07 + 43.76x + 21.26x^2 \pm 4.3 \sqrt{61.01 -228.28x + 347.81x^2 -210.11x^3 + 43.82x^4} \end{align}\]
- R2-3.0T
- Blood (S) \[\begin{align} y =& 22.51 + 6.77x + 30.43x^2 \pm 4.3 \sqrt{210.01 -785.77x + 1197.17x^2 -723.22x^3 + 150.81x^4} \end{align}\]
- Blood (A) \[\begin{align} y =& 13.6 + 45.73x + 13.68x^2 \pm 4.3 \sqrt{115.68 -432.82x + 659.43x^2 -398.37x^3 + 83.07x^4} \end{align}\]
- R2*-1.5T
- Blood (S) \[\begin{align} y =& 81.26 + 31.83x + 42.08x^2 \pm 4.3 \sqrt{103.13 -385.88x + 587.91x^2 -355.16x^3 + 74.06x^4} \end{align}\]
- Blood (A) \[\begin{align} y =& 114.87 -21.53x + 71.94x^2 \pm 4.3 \sqrt{9.3 -34.8x + 53.01x^2 -32.03x^3 + 6.68x^4} \end{align}\]
- R2*-3.0T
- Blood (S) \[\begin{align} y =& 52.47 + 43.05x + 30.38x^2 \pm 4.3 \sqrt{54.16 -202.62x + 308.71x^2 -186.5x^3 + 38.89x^4} \end{align}\]
- Blood (A) \[\begin{align} y =& 54.28 + 39.65x + 36.22x^2 \pm 4.3 \sqrt{10.42 -39x + 59.42x^2 -35.9x^3 + 7.49x^4} \end{align}\]
Additional linear regression for blood
| Var | FS | S.Blood_1 | S.Blood_2 | F.Blood_1 | F.Blood_2 |
|---|---|---|---|---|---|
| R1 | 1.5 | -0.61 (-3.56, 2.34) | 15.15 (12.92, 17.38) | 0.06 (-2.24, 2.35) | 16 (14.26, 17.74) |
| R1 | 3.0 | -0.72 (-2.48, 1.03) | 8.91 (7.59, 10.24) | -0.35 (-1.85, 1.15) | 9.55 (8.41, 10.68) |
95% Confidence limits for regression lines
| FS | Blood | r2 |
|---|---|---|
| 1.5 | F | 0.9965213 |
| 1.5 | S | 0.9936011 |
| 3.0 | F | 0.9958405 |
| 3.0 | S | 0.9934934 |
- R1-1.5T
- Blood (S) \[\begin{align} y =& -0.61 + 15.15x \pm 3.18 \sqrt{0.86 -1.11x + 0.49x^2} \end{align}\]
- Blood (A) \[\begin{align} y =& 0.06 + 16x \pm 3.18 \sqrt{0.52 -0.67x + 0.3x^2} \end{align}\]
- R1-3.0T
- Blood (S) \[\begin{align} y =& -0.72 + 8.91x \pm 3.18 \sqrt{0.3 -0.39x + 0.17x^2 } \end{align}\]
- Blood (A) \[\begin{align} y =& -0.35 + 9.55x \pm 3.18 \sqrt{0.22 -0.29x + 0.13x^2 } \end{align}\]
AMAG vs Sandoz
P-values based on a two-way (group + dose) ANOVA test on group difference.
Knobloch data
For R1, R2 and R2* and under field strength 1.5T and 3.0T, we compare F-Saline & S-Saline vs K-Saline and F-Blood & S-Blood vs K-Blood.
Saline
First compare F-Saline & S-Saline vs K-Saline under linear models. Chi-square tests with 2 degrees of freedom (intercept + slope) are used to compare each pair of regression lines.
