Table 3.
Logistic regression analysis for predicting fatigue after a resistance training protocol, using maximal isometric force (MIF) as a fatigue pattern
| Model | B | Std Error | Wald | gl | p-value | Exp (B) | 95% CI for Exp (B) | ||
|---|---|---|---|---|---|---|---|---|---|
| Inf | Sup | ||||||||
| ∆ VL Vrd90 | −0.109 | 0.044 | 6.157 | 1 | 0.013 | 0.896 | 0.822 | 0.977 | |
| Constant | −3.454 | 1.473 | 5.498 | 1 | 0.019 | 0.032 | |||
|
Model Summary G2 = 15.472; p =0.001; X2HL=1.226 p= 0.976; R2cs = 0.461; R2N = 0 .624 | |||||||||
a. Dependent variable: Fatigue assessed by MIF
b. Predictors: (Constant); ∆ VL Vrd90: relative change from pre- to post in vastus lateralis (VL) radial displacement velocity (Vrd90)