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This allowed for group comparisons and easier descriptions of differences between subjects based on these characteristics.
Finally, a similar GEE analysis was completed to compare IHC staining between subjects based on clinical outcomes.
However, a significant interaction was also observed between subjects based on their use of insulin therapy (P for interaction <0.001).
For men, there was no significant difference in anthropometric indices to discriminate between subjects based on high blood pressure or low HDL.
A 2 × 2 mixed ANOVA (repeated measures within subjects based on factor of condition, i.e., normal saline vs. intralipid; between subjects based on factor of race, i.e., African American vs. Caucasian; and condition × race interaction) was used to analyze glucose; insulin; C-peptide; triglycerides; FFAs; fat oxidation; total, oxidative, and nonoxidative glucose disposal; and insulin sensitivity.
Sex-related differences were analyzed with a 2 × 2 mixed ANOVA (repeated measures within subjects based on factor of condition, i.e., normal saline vs. intralipid; between subjects based on factor of sex, i.e., male vs. female; and condition × sex interaction), combining African American and Caucasian data.
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The elements of the generated distance matrix represent the pairwise distances between two subjects based on demographic and lifestyle variables.
So when we measure the distance (correlation) between two subjects based on 2D space, these highly correlated feature will contribute less than they do at the original feature space.
Associations between groups of subjects based on BHR and EI respectively, as well as risk factors, symptoms and investigations were also assessed.
In recent years, several investigators have reported variations in mRNA levels between patients and control subjects based on peripheral and accessible tissues and also between pre- and post-treatment conditions in major depressive disorder (MDD) and bipolar disorder (BD) [ 5- 11].
The solid mathematical background of these techniques, as well as their successful application in various fields provides confidence in their ability to discriminate between different types of subjects based on large and complex sets of observations.
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