interpreting parameters in multivariate multiple regression

Hi all,

I have a repeated measures multivariate multiple regression. All measures were sampled three times (hence, Time is the within subject factor). There are five dependent measures, and two continuous independent factors which are principal components from a PCA (i.e. they are orthogonal). I call these factors "PC1" and "PC2"

My model include PC1 and PC2 as between subject factors, and Time, Time*PC1, and Time*PC2 as within subject factors. I ditched the PC1*PC2 or any three-way interactions because in this case, they are meaningless.

There is a significant effect of Time, PC2, and Time*PC2 interaction, but NO effect of PC1 or Time*PC1. Hence, I want to examine the effect of PC2 for all three time points.

Given that the analysis has told me there is no effect of PC1 or Time*PC1, should I conduct multiple regressions (i.e. include both PC1 and PC2 in the model) or simple regressions (i.e. bivariate regression between the responses) at each time point?

Thank you!