Sentence examples for separation of variances from inspiring English sources

The separation of variances arising from different experimental factors and from the residual noise is achieved as follows.

Item response theory was used to evaluate differential item functioning, while multi-group mean and covariance analyses enabled the separation of variance components due to the latent inductive reasoning/Gf trait from test bias variance components.

Linear mixed model analyses were used, enabling separation of variance attributable to individual factors and variance attributable to family membership (i.e., family cluster effect).

An important advantage of this type of model is that it allows both offspring and parental trait values to be used to distinguish a number of sources of variation, thereby enabling the separation of additive genetic variance from dominance genetic variance and direct maternal effects [ 42, 49].

ANOVA model consists in a separation of a complex variance term into its components [ 25].

Genetic model fitting of twin data allows for separation of the phenotypic variance into its genetic and environmental components.

Standard varieties connected the different blocks in the sense that they allowed estimation of the inter-block variance and separation of the block from the error variance.

Statistical analysis was performed using CropStat for Windows version 7.2 (IRRI 2007) for standard analyses of variance and separation of main effects and interaction means.

It is based on comparison of the variance covariance matrices in monozygotic and dizygotic twin pairs and allows separation of the observed phenotypic variance into its genetic and environmental components, i.e. additive (A) or dominant (D) genetic components, and common (C) and unique (E) environmental components [ 23].

PC dimension #3, with less total variance than PC #2, has its clearest source of variance with the separation of all the EGFR targets.

A novel approach we use, crucial to our ability to extract results presented here, is the separation of the contributions to the variance from the fluctuating part of an FD (FFD), and the non-fluctuaing part (NFFD).