Statistical Analysis
REGRESSION
We compared the distribution of demographic variables between the trial arms with the chi-square test or the exact Fisher test, as appropriate. Regarding the primary outcome, the sum of the scores is a discrete count, but with a bounded value at the total number of questions (28 knowledge questions). Thus, we modeled the total score using a Beta-Binomial distribution, that is, score∼BB (n=28,μ,σ), which accounts for potential overdispersion and the bounded property of the distribution. Compared to the empirical distribution of the total score, the distribution fitted better than the common count distributions, including Poisson and Negative Binomial distribution (Figure S1 in There were 11 individuals with missing data in one of the 28 knowledge questions; thus, we used multiple imputations to impute the missing values, conducted analyses on 100 imputed samples and reported the pooled analyses. We conducted multivariable regression analyses to explore the effect on the knowledge scores of the SAS Intervention group based on intention to treat. The model was adjusted for age, sex, education level, living area, working status, and whether the mother was enrolled in the MomConnect program. The models were fitted in a Bayesian inference framework using the statistical program R (version 4.0.2; The R Foundation). We reported the 95% uncertainty interval (UI) of the mean differences between the covariates by drawing 1000 samples from the posterior distribution and calculating the quantiles of the mean difference, which is nμ for the BB distribution. (The code for analyses is publicly available at GitHub [