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We also explored the use of a quality control matrix designed to manage missing values and to identify unreliable results for repeat analysis.
Results from all qPCR reactions were assessed using a quality control matrix designed to manage missing values and to identify unreliable results for repeat analysis.
62 Imputation was not used to manage missing values.
Imputation approaches to manage missing data made no difference to the results.
We used a conservative approach to manage missing data, by not including cases with missing information in the analysis.
If ignorable missing can be justified, an alternative approaches to handle missing values are to apply multiple imputation [ 17, 19] or the multi-step transition probabilities [ 8].
The method is also model-free, manages missing values without imputation techniques (i.e., pair-wise feature correlations can be estimated by excluding only samples with missing values), robust to data noises and provides effective visualization tools.
This study uses an imputation-based approach to handle missing values in microarray data.
7 Mean imputation was used to manage missing data.
Approaches to managing mode feature effects are discussed.
The present study showed that nested imputation methods are suitable approaches to deal with missing values in both continuous and categorical background variables.
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