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19 20 21 Seven domains were assessed: confounding, selection, exposure measurement, misclassification over time, missing data, outcome measurement, and selective reporting.
We imputed missing data (outcome, exposure, covariate) by cohort, using multiple imputation by chained equations (ICE) (Rubin 1987; van Buuren 2007), and performed pharmacokinetic model simulations for each imputation set.
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Based on the extent and nature of missing data (outcomes, predictors, baseline, and items from scales), we will use one of several strategies for data analysis.
Although every effort was made to obtain missing data (outcomes, study design) from the trial authors, it was not possible in every case to obtain these data; the included studies are therefore not represented fully in the meta-analyses.
There were no missing data in outcome variables.
Not all mother-offspring pairs were included in analyses because of missing data, mostly outcome data.
If the missing data affects outcome measure, the participant will be rejected.
Missing data on outcome were not imputed and complete case analysis was performed in all cases.
In individual analyses, numbers may be lower due to missing data on outcome measures.
There were also missing data on outcome variables ranging from 1.7 to 3.4%%.
The assessors who contacted the participants to collect missing data on outcome measures and the research staff who input data were blinded to allocation group.
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