These models include variance components for environment and polygenes.
The Bayesian approach allows us to get easily standard error estimates of all parameters in the model, including variance components and their ratios.
Heterogeneity of variances was corrected using general least square (GLS) models including the 'varIdent' variance structure (different variance per factor level, this R-function is found in the 'nlme' package (Pinheiro et al. 2009).
This is a linear model that includes variance components to model the phenotypic similarities within a family, i.e. between the twins.
The model also included variance components, r0 representing variation associated with differences between individuals within practices, u00 representing variation associated with differences between practices and e representing random (measurement) error.
All models included a variance function to take into account variance dependence on fitted values.
The author's emphasis is on providing a unified treatment of linear models, including analysis of variance models and regression models, based on projections, orthogonality, and other vector space ideas.
Different statistical models, including analysis of variance [ 46], linear regression [ 35], and their generalizations such as penalized regression [ 47], have been considered before.
Thus, we were left as best covariance structure model with either the model including 'sex.family' and 'family (4 VCs)' or the model including 'food.family' and 'family (4 VCs)', both models including the four variance components for the crosses.
The general linear model incorporates a number of different statistical models, including analysis-of-variance (ANOVA) and multiple regression analysis.
