Table 2.
Results of multiple linear regression analyses. Given are: R2 values and p-values for overall regressions on dependent factors Y, regression coefficients A1 and A2 (± 95% confidence intervals) corresponding to dependent factors X1 and X2 (either GAG & COL or Day and ρ), and p-values for each factor X1 and X2.
Y | R2 | p (total) | A1 (kPa) [X1 = GAG] |
p (X1) | A2 (kPa) [X2 = COL] |
p (X2) |
EY | 0.78 | <0.0001 | 41.8±3.2 | <0.0001 | 6.1±10.4 | 0.56 |
G* | 0.83 | <0.0001 | 156.2±10.9 | <0.0001 | 82.0±35.5 | <0.05 |
Y | R2 | p (total) | A1 (kPa·day−1) [X1 = Day] |
p (X1) | A2 (kPa·mL·cells−1) [X2 = ρ] |
p (X2) |
EY | 0.57 | <0.0001 | 0.52±0.30 | 0.08 | 1.81±0.17 | <0.0001 |
G* | 0.51 | <0.0001 | 3.3±1.3 | <0.05 | 6.69±0.72 | <0.0001 |
Y | R2 | p (total) | A1 (%/ww·day−1) [X1 = Day] |
p (X1) | A2 (%/ww·mL·cells−1) [X2 = ρ] |
p (X2) |
GAG | 0.68 | <0.0001 | 0.014±0.007 | 0.066 | 0.04±0.003 | <0.0001 |
COL | 0.19 | <0.005 | 0.0068±0.0036 | 0.065 | 0.0061±0.0017 | <0.001 |