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Despite the efforts made to reduce their occurrence, in most cases missing values cannot be avoided.
Most (5/10) missing values occurred during the occlusion phase of the experiment.
There were at most two missing values from each set of 423 values (per variable).
These were excluded from further analysis, leaving 369 SNPs with at most 15 missing values.
Genes with at most 15% missing values were allowed in the final dataset.
The last observation carried forward approach was used most often: missing values were replaced by the last value observed.
Besides, most methods estimate missing values without considering the imputation sequence among incomplete genes.
From the examined quantitative genetic applications, association mapping profited most from imputing missing values.
(Most of the missing values occur in the variables representing SNPs).
Most questionnaires contained no missing values.
Most questions contained few missing values.
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CEO of Professional Science Editing for Scientists @ prosciediting.com