2.3. Statistical Analysis
REGRESSION
Analyses were performed on an intention-to-treat basis; all children who consented to participate in the 7-year follow-up were analyzed according to the original group to which they were allocated, whether they completed the assessments or not. The primary analysis was based on imputed data and included all participants who consented to the follow-up study. To assess missing outcome data, multiple imputation was performed separately by treatment group using chained equations to create 100 complete datasets under the assumption that data were missing at random [Normally distributed outcomes were analyzed using linear regression models, with the effect of treatment expressed as a mean difference with 95% confidence intervals (CI). Binary outcomes were analyzed using log-binomial models, with the effect of treatment expressed as a relative risk with 95% CI. All models used generalized estimating equations to account for the clustering of infants within mothers. Both unadjusted and adjusted analyses were performed, with adjustments made for sex and birthweight of the child and study center. Because unadjusted and adjusted analyses did not differ markedly, only adjusted analyses are presented. Secondary analyses were performed to test for evidence of effect modification by the sex and birthweight (<1250 g and ≥1250 g) of the child. Statistical significance was assessed at the two-sided 