Table 2 Comparison of linear and non-linear regression analysis of changes in running speeds across years in the annual fastest women and men to determine which model is the best
From: Will women outrun men in ultra-marathon road races from 50 km to 1,000 km?
Running speed | Kind of regression | Sum of squares | DOF | AICc | Best regression | Best regression | Delta | Probability | Likelihood |
|---|---|---|---|---|---|---|---|---|---|
AIC-Test | F-Test | ||||||||
Annual fastest men 50 km | Polynomial | 45.22 | 29 | 17.22 | Polynomial | Polynomial | 12.99 | 0.0015 | 99.8% |
Linear | 77.31 | 31 | 30.22 | ||||||
Annual fastest women 50 km | Polynomial | 33.46 | 30 | 4.86 | Polynomial | Polynomial | 6.30 | 0.041 | 95.9% |
Linear | 43.38 | 31 | 11.16 | ||||||
Annual fastest men 100 km | Polynomial | 29.45 | 44 | -16.02 | Polynomial | Polynomial | 45.56 | 1.27 e-10 | 100% |
Linear | 85.81 | 47 | 29.54 | ||||||
Annual fastest women 100 km | Polynomial | 14.83 | 37 | -33.57 | Polynomial | Polynomial | 38.62 | 4.10 e -09 | 100% |
Linear | 47.05 | 42 | 5.04 | ||||||
Annual fastest men 200 km | Polynomial | 3.30 | 0 | 4.15 | Linear | Undetermined | 22.70 | 1.17 e -05 | 99.9% |
Linear | 4.99 | 15 | -18.54 | ||||||
Annual fastest women 200 km | Polynomial | 0.011 | 0 | -27.78 | Polynomial | Undetermined | 26.48 | 1.77 e -06 | 99.9% |
Linear | 2.92 | 4 | -1.30 | ||||||
Annual fastest men 1,000 km | Polynomial | 1.65 | 0 | 1.39 | Linear | Undetermined | 2.24 | 0.24 | 75.4% |
Linear | 5.15 | 6 | -0.84 | ||||||
Annual fastest women 1,000 km | Polynomial | 1.08 | 0 | -4.19 | Linear | Undetermined | 9.72 | 0.0076 | 99.2% |
Linear | 1.93 | 8 | -13.92 |