Sentence examples for multivariate multiple imputation from inspiring English sources
We used multivariate multiple imputation to impute missing variables (mostly outcome data) for participants with measures of weight in pregnancy (n = 12,447), including all exposures, covariables, outcomes, and potential predictors of missing data in the imputation equations (see online supplement) (12).
To address this, we used multivariate multiple imputation to impute missing information on outcomes and covariables for otherwise eligible maternal offspring pairs with valid maternal 25(OH D measures from pregnancy and who had attended the year 9.9 or 15.4 assessments.
To increase efficiency and minimize selection bias, we used multivariate multiple imputation 25 to impute missing values of covariables for eligible participants (see also Online Repository).
Furthermore, the main findings of this study were reproducible in the total cohort with missing values imputed using multivariate multiple imputation methods.
This was imputed using a multivariate multiple imputation procedure with 10 imputations.
Missing data will be imputed using a multivariate multiple imputation procedure (Solas 3.0).
Missing covariate data were replaced using multiple imputation (imputed datasets: N=30) applying multivariate chained equations as described for use in the Cox model.
Multiple methods have been developed in order to deal with missing data, including single imputation, multiple imputation, multivariate imputation by chained equations (MICE), nearest neighbour estimation and missForest.
Multiple methods have been developed in order to deal with missing data, including single imputation, multiple imputation, multivariate imputation by chained equations (MICE), 3 nearest neighbour estimation (NN), 4 and missForest.
Once we had identified variables for further evaluation in the multivariate model, we used multiple imputation for variables with missing observations.
Missing values for duration of caregiving (missing value in 7 cases) and income (missing value in 342 cases) were supplemented in the multivariate analysis using the multiple imputation by chained equations (MICE) command in Stata [ 56, 57].
