A Redundancy Analysis with Multivariate Random-Coefficients Linear Models

Random-coefficients linear models can be considered as a particular case of linear mixed models, in which the random effects depend on the model fixed- effects design matrix. A Redundancy Analysis of estimates of the multivariate random- effects may be able to capture the leading contribution to this correlation. Starting from the standardized multivariate best linear predictors, we introduce the random effects reduced space by a weighted least-squares closed-form solution. The application shows the effect of the linear dependence of the random-effects in the space of the predictor variables.