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Missing data were imputed for discrimination and CES-D using the individual mean imputation method, which imputes a value based on how a subject responds to other questions.
Missing data were handled using the mean imputation method [ 36].
The WOMAC method is a variant of a standard mean imputation method.
In case of missing values we applied the mean imputation method.
In the main analyses, the mean imputation method was applied because only 6 subjects had ≤ 2 DK responses in the child section.
Missing genotypes were estimated with the mean imputation method implemented in the "rrBLUP" package and the proximity matrix method implemented in the "randomForests" package.
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The use of mean imputation methods would have required a careful evaluation of linearity and possibly data transformation due to the nonlinear pattern observed in ASRM and QIDS scores (Moore et al. 2012a, b).
Examples of single imputation methods include hot deck, cold deck method, mean imputation, regression technique, last observation carried forward (LOCF) and composite methods which uses a combination of the above methods to impute missing values.
Popular single imputation methods are last observation carried forward and mean imputation.
Methods include: last-observation-carried-forward imputation, regression mean imputation, and multiple imputation.
Missing data for weight change will be addressed using a conservative 'baseline-value carried forward' approach and examined in a sensitivity analysis using group mean-imputation methods to confirm the robustness of results [ 37].
More suggestions(15)
mean imputation process
mean shift method
mean imputation panel
mean imputation accuracy
mean square method
mean score method
mean difference method
mean calculation method
mean imputation regression
mean center method
mean centering method
mean ref method
mean imputation r
mean normalization method
mean imputation adopted
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