Model | -2 log likelihood | AIC | BIC | Regression equation Y = b0 + b1 × X + b2 × X2 | p-value | ||
---|---|---|---|---|---|---|---|
b0 | b1 | b2 | |||||
1 | 699.7 | 703.7 | 706.0 | Y = 8.3047 + 0.09863 × Xc | < 0.001 | < 0.001 | - |
2 | 670.4 | 678.4 | 682.9 | Y = 8.2525 + 0.09874 × Xc | < 0.001 | < 0.001 | - |
3 | 706.7 | 710.7 | 713.0 | Y = 7.8581 + 0.09019 × Xc + 0.00058 × Xc2 | < 0.001 | < 0.001 | 0.004 |
4 | 673.6 | 681.6 | 686.2 | Y = 7.8134 + 0.08553 × Xc + 0.00066 × Xc2 | < 0.001 | < 0.001 | 0.002 |
2.1 | 670.4 | 678.4 | 682.9 | Y = 3.3157 + 0.09874 × X | < 0.001 | < 0.001 | - |
SE(b1) = 0.008011 95% CI of β1 = (0.08212, 0.1154) |