  This paper explores a variety of topics related to the question of testing
the equality of covariance matrices in multivariate linear models, particularly
in the MANOVA setting. The main focus is on graphical methods that can be used
to address the evaluation of this assumption. We introduce some extensions of
data ellipsoids, hypothesis-error (HE) plots and canonical discriminant plots
and demonstrate how they can be applied to the testing of equality of
covariance matrices. Further, a simple plot of the components of Box's M test
is proposed that shows _how_ groups differ in covariance and also suggests
other visualizations and alternative test statistics. These methods are
implemented and freely available in the **heplots** and **candisc** packages
for R. Examples from the paper are available in supplementary materials.
