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Lineage-specific nucleotide substitution rate variation (summed branch lengths root-to-tip) for all 26 taxa and 83 CNE genomic regions (after excluding datasets with high proportions of missing data or any missing taxa), was visualised with a Principal Component Analysis (PCA).
The variety of datasets allowed the procedures to be investigated for different proportions of missing data and for different missing data patterns.
However, this approach is only appropriate for small proportions of missing data.
Proportions of missing data for both background variables X1 and X2: m(X1) = {.25,.4} and m X2) = {.25,.4}.
Higher proportions of missing data for background variable X1 caused a bias in the estimation of β2.
Finally, as noted earlier, there is substantial missing data on income in all countries and the range of the proportions of missing data, 15 42%, is considerable.
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Low-coverage shotgun sequencing also yields a high proportion of missing data.
Fortunately, the proportion of missing data in the ED registers in this hospital was small.
Poland, Japan, Estonia, Ireland and Korea have the highest rates of missing data as opposed to the Netherlands, the U.S., Canada and Norway, where the proportion of missing data is smallest.
Moreover, there was a relatively high proportion of missing data from the initial study population.
A high proportion of missing data significantly decreases the sample size available for statistical analysis, and consequently decreases statistical power.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com