2.7. Statistical Analysis
fatigue
SECONDARY
Sample size calculation was conducted using three 1-β power values (0.80, 0.95, and 0.99), a significance threshold value of α equal to 0.05, and three effect size values (Cohen’s f The effects of the treatments on the response variables (fatigue level, quality of life, and fatigue-associated biomarkers) were assessed through a linear mixed model (LMM), where the treatment (placebo and food supplement), the measurement times [i.e., at baseline (t0), after 28 days of treatment (t1) and after 56 days of treatment (t2)], and the age and sex of the subjects were entered into the model as fixed effects. The measurement × treatment interaction was also included among the independent variables. This interaction is the key variable for the primary endpoint, as it allows testing whether the trends for the placebo and food supplement treatments differ over the course of the measurement period. The identity of the subject was evaluated as a random effect, which provided control for differences between the enrolled subjects, regardless of fixed effects and their interactions. The same model was used for the analysis of the chemical biomarkers related to the secondary outcome. In this case, an independent LMM was run for each biomarker, where the fixed and random effects were the same as for the previous analyses. Analyses were performed using the lme4 [