Analysis
REGRESSION
All analyses were performed by using IBM SPSS Statistics for Windows (version 26 Armonk, NY: IBM Corp). Normality was assessed and a natural logarithm transformation was applied for skewed variables. To investigate the effect of leucine supplementation (Treatment) at 8 weeks on body composition and fasting metabolic parameters, we performed an analysis of covariance (ANCOVA) (via General Linear Model (GLM) univariate procedure in SPSS), using the outcome variables at 8 weeks as the dependent variable, with an adjustment of the baseline values. In our analyses, age, gender, phase and energy deficit, kJ/d were adjusted as confounders and two potential interaction effects between treatment and gender (treatment*gender), and between treatment and phase (1 & 2) (treatment*phase) were assessed in the ANCOVA. The study was conducted in 2 phases (spring-summer (Phase 1) and Autumn-winter (Phase 2) for feasibility of clinical trial, which differed in season, gender distribution and we were interested in knowing if that has any potential difference to the outcome. As normality could not be achieved even after transformation for several outcome variables, bootstrapping method with 1000 bootstrap samples was used for deriving robust estimates of standard errors, regression coefficients and corresponding 95% confidence intervals. A 