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We acknowledge that it is highly debatable to impute large shares of missing data, but we argue that it is reasonably safe to assume these values to be missing at random because the missingness is design-based and not due to (possibly selective) non-response.
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Figure 5 shows that the percentage of missing data on education level in each year becomes more homogenous based on imputed data compared with the shares of missing observations in the original data.
Also called the rate of missing information, it differs from the percentage of missing data.
Percentage of missing data, by locus.
The percentage of missing data was <10%.
Due to the size of this dataset many taxa suffer from large amount of missing data, but all share at least one mitochondrial or nuclear gene, thus avoiding the problem of non overlapping sequences [ 142].
*presence of missing data, adjusted percentage.
To limit the proportion of missing data, we selected for analysis the protein-coding genes that are shared by at least eight taxa.
White-colored grid boxes represent regions of missing data.
The rate of missing data was 2.4%.
Since the amount of missing data were low, no assumptions were made for missing data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com