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There was no problem with collinearity in the proposed model (maximum Variance Infamation Factor (VIF) = 1.18).
Multicollinearity was present only at a moderate level throughout the analyses; in the fully adjusted model, maximum variance inflation factor was <1.42 for women and <1.30 for men, suggesting that jointly explained variance would not greatly interfere with the interpretation of partial beta weights.
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Among the models although the 6-factor model had the maximum variance explained (53.9%), when we looked at the the most parsimonious models it was the 3-factor (36.9%) and 2-factor models (30.5%).
For all investigated markers (except D-loop and G3PDH) the three-population-model showed the maximum variance between groups and the lowest among populations within each group (Table 2).
This model gives those miRNAs explaining the maximum variance in GE profiles by ensuring a good fit of the model.
It minimizes the maximum variance of the predicted value of the regression model.
The maximum variance explained was 69% (Table 4) and the predictive models (without controlling for phylogeny) explained 30% of the variance and prediction accuracy was 77% (Table 3).
The shape model is trained employing Principal Components Analysis (PCA) on the aligned training shapes to find the eigenshapes of maximum variance and the mean shape s0.
Just look at one direction which we have the maximum variance.
Purposive sampling was employed for maximum variance.
Thus, a mixed model estimating variance components using restricted maximum likelihood was used to assess the within- and between-subject variance components in whole blood, plasma, and urine (MnB, MnP, and MnU, respectively) in a group of nine newly-exposed apprentice welders, on whom baseline and subsequent longitudinal samples were taken over a three month period.
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