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The use of national administrative data to define variables meant that we considered there was a limited amount of missing data, because patients could be tracked even if they moved out of the Birmingham area, provided that they remained within England.
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Prudential Life Insurance data set has attributes with a remarkable amount of missing data.
The biggest differences were observed with RCT 9, which had a large amount of missing data.
Furthermore some birth cohorts have a substantial amount of missing data [15].
First, we have a substantial amount of missing data.
Thus, there is a notable amount of missing data.
There was a minimal amount of missing data (<5%) and missing points were imputed.
These variables had a minimal amount of missing data with, at most, 3.5% missing for the motivation variable.
There was a small amount of missing data on place of residence.
There was a substantial amount of missing data concerning the adverse effects in these studies.
There was a trivial amount of missing data (<1%) for all variables except age (14%).
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