Variance Component Analysis
Description
ANOVA-type estimation (prediction) of random effects and variance components in linear mixed models,
is implemented. Random models, a sub-set of mixed models, can be fit applying a Variance Component Analysis (VCA).
This is a special type of analysis frequently used in verifying the precision performance of diagnostics.
The Satterthwaite approximation of the total degrees of freedom is implemented. There are several functions
for extracting, random effects, fixed effects, variance-covariance matrices of random and fixed effects.
Residuals can be extracted as raw, standardized and studentized residuals. Additionally, a variability chart
is implemented for visualizing the variability in sub-classes emerging from an experimental design ('varPlot').