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These items belonged to the 'Driving' subscale with a high percent of missing data (73.3 %), 'Distance activities' (Going out to movies/plays/sports events), 'Mental health' subscale (Embarrassment) and 'General health'.
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However, several limitations of these data have been documented, including a high percent of missing information and an underestimate of timing of the first prenatal visit and total number of visits [ 25].
There was a higher percentage of missing data for secondary outcomes, but no scale had more than 20% missing data.
The inclusion and exclusion criteria resulted in a large percent of missing data for women offenders (a 3.7%% under sampling for the group when compared to the total population).
The 'Missed' group was excluded from the analysis as there was a high degree of missing data.
Although the percent of missing data in the former was relatively high, we decided that the bias introduced by restricting the analysis to those observations with complete data would be larger than that caused by imputing missing data combined with appropriate uncertainty analysis [ 62].
For the six items used to measure Beliefs, the percent of missing data ranged from 11.7 to 12.7%%.
The number of completed items, the percent of missing data in every item and the frequency distribution of individual items were determined.
The number of alleles per marker and percent of missing data were calculated for the remaining 380 genotypes with 34 markers (Table 2, Additional file 4: Table S4).
The data contain a higher fraction of missing data compared to the small data set.
Moreover, there was a relatively high proportion of missing data from the initial study population.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com