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The scaled data for liquid kill velocities appear to support the field data.
Other markers were tested by determining their added value on two models: firstly to a model using only prior risk and additionally to a model using prior risk and scaled data for PAPP-A and f β-hCG.
Next, to visualize the changes in metabolite levels during aging, we performed hierarchical clustering on both within-group and between-group scaled data for all signals commonly changing with age in both diets.
We opted to use scaled data for PAPP-A and f β-hCG in this comparison as the data used for the other markers was also obtained using scaling, thus allowing a consistent workflow for all data.
Differences in gene expression between T0 and T12 were evaluated using paired Student t tests after processing of the scaled data for elimination of the genes with a flag absent in more than half of the samples and selection of the 8,000 genes that displayed the widest inter-individual variations in the remaining genes.
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Outcomes for the studies included were reported using both scales and individual items, although for the effect size calculations were restricted to scale data for knowledge and attitudes.
Some attention has been devoted to the problem of estimating backgrounds, scaling data for dataset merging, and determining statistical significance of intensity differences or ratios.
The data were analyzed by logistic regression for scaled data.
The above scaled data were also used for k-means clustering analysis using k = 10.
PEG is widely used; however, large-scale data for PEG have been lacking.
It offers the most significant look to date at the use of such large-scale data for law enforcement, rather than for national security.
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