4.4.3 Data Analysis: The intention-to-treat principle will be applied, including all randomized infants for each outcome. For comparison purposes, results will also be evaluated in terms of the dose actually received. Should baseline imbalances occur between groups despite randomization, these will be treated as covariates and adjusted for. To compare proportions between treatment groups, sample proportions will be evaluated by a Chi-squared test of proportions, adjusted for multiple comparisons to ensure a family-wise error rate of 0.05. Results will be assessed at the each time point, with a Chi-squared test for trend in proportions to compare their temporal evolution. Mean 25(OH) D concentrations, bone mass, and biochemical indices of bone remodeling will be compared in each dose group under a fixed effects ANOVA model, with significant group differences localized by suitable post-hoc testing (e.g. Tukey method), again with adjustment for multiple comparisons to ensure a family-wise error rate of 0.05. Time course will be evaluated under a mixed effects ANOVA model (with the addition of time as a random effect). The dynamics of the 25(OH)D-PTH relationship is visually assessed in linearized log-log plots, whose slope is a measure of PTH sensitivity to 25(OH)D. The best-fit line is determined by least squares, and slopes compared by standard methods based on the distribution of regression coefficients as t-statistics. Taking the following as independent predictor variables - dose, source of vitamin D, age, gender, season of birth, ethnicity, and baseline vitamin D stores - their effect on the likelihood of achieving our therapeutic target will be evaluated by multiple logistic regression, with ordinary multivariate linear regression to examine their impact on serum concentration of 25(OH)D, bone mass, osteocalcin, and N-telopeptide.