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Expectation-Maximization (EM) followed by a multiple imputation procedure was applied to impute the missing data [ 39].
Missing data was reconstructed by a multiple imputation based on several personal characteristics, which were investigated by means of a questionnaire before the curricular unit.
43 Missing data will be addressed by a multiple imputation approach to reflect the uncertainty present when replacing missing data.
Afterwards, missing values were replaced by a multiple imputation based on expectation maximization (EM) algorithm with the statistical software NORM 2.03 [ 19].
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In our final analyses, we examined the robustness of the associations, first by changing the categorization of 2 risk factors and second by conducting a multiple imputation to address the missing data for 861 children.
We dealt with results < LOD by using a multiple imputation method (Lynn 2001) along with the SAS procedure PROC MIANALYZE, which summarizes parameter estimates and incorporates the resulting uncertainty associated with the multiple imputations used to obtain them.
Missing BDI-II and BAI values were imputed by means of a multiple imputation procedure [ 43] using the automatic method in SPSS 21.0.
Missing information for covariates led not to exclusion, but was addressed by means of a multiple imputation approach.
A sensitivity analysis will be conducted by means of a multiple imputation analysis (based, among others on HbA1c scores of the population at T1) and an analysis based on a Last Observation Carried Forward (LOCF) imputation.
Missing data were imputed using a Multiple Imputation by Chained Equation (MICE) approach to obtain a full dataset [ 21].
Missing values for prognostic variables were imputed using a multiple imputation by chained equation (MICE) approach (Van Buuren and Groothuis-Oudshoorn, 2011).
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