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One can view this approach as an extension of the mean imputation adopted by the CE estimator.
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In our examples, we have used the mean imputation to impute missing markers.
We imputed missing baseline data using regression or mean imputation.
11 Mean imputation is one of the most naive and easiest methods for imputing missing values.
We tried the zero imputation method, which Debray et al. adopted [ 6] and called uninformative regression coefficients, but it did not show notable results compared with the results from M2 (mean imputation).
The study also compared the proposed imputation approach with mean imputation and other three KNN imputation approaches.
Mean imputation was used for a few missing values due to signal interference caused by animal movements.
Based on a comprehensive set of carefully controlled experiments, we conclude that Bayesian multiple imputation and regression imputation are the most effective techniques, while mean imputation performs extremely poorly.
These approaches are advantageous to traditional techniques (e.g. deletion and mean imputation techniques) because they require less stringent assumptions and mitigate the pitfalls of traditional techniques.
The missing data imputation method used here utilizes the bounded conditional mean imputation (BCMI) as proposed in [19].
Mean imputation was used to replace missing data (6 out of 270 data points were missing).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com