Concerning the impact of variability, both numeric and subjective evaluations pointed to no positive effects on considering spatiotemporal variability into our representation model, and that the proposed representation of variability, at the optimal metric resolution, offers only some extent of the variance observed in the analyzed dances.
Therefore, in a sensitivity analysis, we analysed the data with multi-level logistic regression analysis, in which variation in outcomes was apportioned to the patient admission and hospital level., Based on the total variance, we calculated intra-class correlations (ICCs), which give an indication of the extent of the variance between hospitals.
Additionally, inspection of the pairwise plots of the other principal components contributing to a lower extent to the variance of the data revealed more contrast clusters.
The same is likely to be true of the face-to-face tutorials however, although the absence of any lasting artifacts from these group discussions makes it harder to establish the extent of this variance and one has to rely upon student self-reports as to the scope and scale of their contribution to group learning activities.
The extent of this variance may be due to:1) stochastic effects resulting from different genealogical histories of each of these segments; 2) the effect of selection; or 3) heterogeneity in the mutation rate among loci [ Chuang and Li, 2004; Matassi et al., 1999].
Using the multiple trait-multiple interval mapping model, these QTLs explained a larger extent of the phenotypic variance for the target traits compared with previous studies.
However, based on the extent of the respective variance components and the criteria of model fit, the set of level I variables mentioned above appeared to account for most of the outcome variance and provided the best fit between observed and expected data.
When establishing the number of factors, the Eigen value (Eigen value > 1: Kaiser's criterion) was taken into account, beside the extent of explained variance, the shape of the scree plot and the possibility of interpreting the factors.
For a given sample size of a given genetic background and for a given QTL detection method, the power of QTL detection depends on trait complexity, the extent of phenotypic variance of the trait, and the genetic parameters of the trait (heritability and the proportion of additive vs. non-additive variance).
For each multiple linear regression analysis, we report the extent of variance in the criterion explained by the regression (R), the significance of the explained variance (F-test), and which predictors significantly contributed to this explained variance (β-weights).
COMPARE reports the slope of the regression line and the extent of variance in the data explained by the regression as compared to a random line.
