2.5. Statistical Analysis
mixed-fed, breast milk, CMPA
REGRESSION
Sample size calculation for the A.R.T. study has been described previously [All statistical analyses were conducted using the SPSS statistical software for Windows (IBM, version 28.0; IBM, Armonk, NY, USA). The normality of the distribution of continuous variables was tested by the Kolmogorov–Smirnov test. Normally distributed continuous variables are presented as means and standard deviations (SD), while non-normally distributed ones are presented as medians and interquartile ranges (IQR). Categorical variables are presented as frequencies (Both per-protocol (PP) and intention–to–treat (ITT) statistical analyses were performed. Between-group differences of continuous variables were tested using either one-way Analysis of Variance (ANOVA) or the non-parametric Kruskal–Wallis test for normally and non-normally distributed variables, respectively. The significance of the association between categorical variables was examined using the chi-squared (χ²) test or the Fisher exact test, whenever appropriate.The incidence (%), relative risk (RR), and the 95% confidence interval of the RR (95% CI) were calculated for the occurrence of AD and CMPA within the first six months of life. Furthermore, a Poisson General Equation Estimation (GEE) regression analysis was performed to calculate the treatment × time interaction effects on the incidence of AD and CMPA in the pHF or SF groups compared to the EBF group (Model 1). The GEE regression analysis was also stratified for the family history of AD (Model 2) and the amount of breast milk consumed by the mixed-fed infants in the pHF and SF groups (Model 3). In all GEE regression models, adjustments were also made for a wide range of potential confounding factors.Repeated measures ANOVA was used to examine the between-group differences (treatment effect) in infants’ growth indices (i.e., body weight, length, BMI, and their Z-scores) at baseline, 4 and 6 months of age; the within-group changes (time effect) from baseline to the follow-up time-points in each treatment arm; and the differences among treatment arms in the changes from baseline to the 6-month follow-up (treatment × time interaction effect). Adjustments were made for the potential “confounding effect” of gender, infant’s birth weight, maternal and paternal educational level, region of residence (i.e., urban vs. rural), and the country of the infant’s birth.All reported 