This approach and these results assume a constant correlation between any two observations from the same dog. This assumption is unlikely because, typically, when you have repeated measurements over time, the data from the same subject at two different points in time are temporally correlated. In principle, observations that are collected at times that are close together are going to be more similar to one another than observations that are far apart.

This motivates an alternative approach, which is to treat this situation as a Multivariate Analysis of Variance problem instead of an Analysis of Variance problem.