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The relationship between different experimental parameters and mean residence time and mean centered variance was examined.
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where f w is the probability density function of a complex normal law centered and variance σ w 2, given by f w ( x ) = 1 π σ w 2 e - | x | 2 ∕ σ w 2, (10).
We used the in-built Matlab functions to perform the analysis using various distance measures e.g. Euclidean, city block etc., on the mean centered and variance scaled expression matrix.
Between-center heterogeneity was quantified using the between-center variance of effect estimates, τ.
Individual BMI was a factor influencing the between-center variance in men (p = 0.002).
This information is used to construct the prior distribution of the between-center variance.
The ratio of the between-center variance to within-center variance differed among the constituents, and for S in PM2.5 and PM10 the between/within area variance were 63 and 31, respectively (see Supplemental Material, Table S2).
The mean all-center variance of the WBC was 2.8 × 10/l and of ESR was 52.5 mm/h, whereas the between-center variances were 0.2 × 10/l and 52.5 mm/h.
To interpret the contribution of between-center variance, we used two approaches, the variance partition coefficient (VPC) and the coefficient of variation (CV) between centers.
In addition, the remaining between-center variance in protein biases (CV = 2.6%) was not significant anymore and no center appeared to deviate from the mean bias.
Then: which leads to: Assuming centers are of equal sizes, ∀ j = 1,..., Q, and we have: where V1 is the between-center variance for sizes of group 1.
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