2.4. Statistical Analysis
diarrheal
Statistical analyses were performed in R (Beta diversity, defined as partitioning of diversity among communities, which is characterized using the number of species shared between communities, was determined by principal coordinates analysis (PCoA) of weighted UniFrac distances in QIIME based on age, residential location, and intervention arm. The ellipse R package, V3.3.2 was used to generate 95% confidence intervals and differences were determined using Adonis with 1000 permutations in the vegan R package V3.3.2. Temporal changes in overall alpha and beta diversity measures and taxon-specific relative abundances of the microbiota of all children in both locations and all three intervention arms were analyzed using a linear mixed-effects model (see below). Relative abundances for selected taxa were modeled as a function, of age adjusting for gender, residential location, and reported diarrheal episode.To estimate the age-specific change in alpha diversity indices and relative abundance of major taxa and the degree of change at a group level, accounting for potential serial autocorrelation in the repeated measurements, the separate linear mixed-effects models were fitted to individual trajectories. Each model described outcomes as a function of time with age in days as a random variable and with gender, residential location, and diarrheal episode as fixed effect covariates using the lmer function of the lme4 R package, v3.3.2. Based on the model results, the 3-monthly rate of change for each outcome along with the lower and upper limits of their 95% confidence intervals (CI) were estimated.The linear discriminant analysis effect size (LEfSe) algorithm was used to identify differentially abundant taxa in children in the first and second years of life combined or at each 3-monthly time point, by residential location and by intervention arms, using default parameters [