The phrase "a common variance in" is correct and usable in written English.
It can be used when discussing a shared difference or variation within a particular context or among a group of items or subjects.
Example: "There is a common variance in the results of the experiments conducted across different laboratories."
Alternatives: "a typical variation in" or "a frequent difference in".
BayesCπ simultaneously performs variable selection and shrinkage of SNP effects remaining in the model with a common variance, although empirical studies in plants have not proven it superior to the simpler RR model [ 9, 28].
Method Bayes-C assumes a common variance for all SNP in the model and is less sensitive to the prior for genetic variance e.g. [ 21- 23] compared to Bayes-B as described by Meuwissen et al. [ 24].
The phenotypic values of a quantitative trait is assumed to be: y = Xg + Zf + e, where y = vector of phenotypic values, g = effects of SNP genotypes, X = model matrix of g, f = random family effects with a common variance σf for sibs in the same family that could include common genetic and environmental effects, Z = model matrix of f.
First, motivated by the application in Section 5, we assume a common variance of error for all genes in study k.
A common variance term applies genome-wide for divergence in transformed allele frequency, and as predicted by theory, the resulting distribution is well approximated by the normal curve (fig. 3).
This evaluation consists of two components, assessing the capacity of a common variance estimate to explain the observed gene sample variances and evaluating how improving this common variance estimate can aid in the detection of differentially expressed genes.
Factor analysis places together closely related items to form a smaller number of "latent variables" (factors) explaining the maximum amount of common variance in a correlation matrix.
The goal is to achieve parsimony by using the smallest number of explanatory concepts to explain the maximum amount of common variance in a correlation matrix [44].
A similar process was used as a second purpose, which was to generate a global factor for ECF, identifying the common variance in the Digit Forward, Digit Backward, SCWT I, SCWT II, SCWT III, COWAT – FAS, and COWAT – Animals tests, due to their mentioned similarity in terms of cognitive constructs.
