I would be most grateful for any thoughts on the following:

I have a cross-sectional dataset with 7 outcome variables from 100 subjects. The outcome variables are of equal theoretical priority and are moderately correlated. I chose MANCOVA because I am interested in the effect of the predictors not only on the individual outcome variables but also on "a linear combination" of the outcome variables.

I have two predictor variables which are both continuous, so in SPSS MANOVA I enter these as covariates. Both give a significant main effect.

As I understand, there are two ways to follow up a significant MANOVA/MANCOVA:

1. Simply look at the tests of between-subject effects that follow the multivariate tests.

2. Normally, discriminant analysis, as I understand from Tabachnick and Fidell, is a different (better) way to follow up a significant MANOVA because it is more "in the spirit" of MANOVA - taking advantage of linear combinations of dependants. However, I have no grouping variable, so discriminant analysis is not possible.

Question: How can I follow up on a significant multivariate test to demonstrate the relative contribution of each dependent variable to the linear composite that give the significant multivariate effect if my predictors are continuous? Is MANCOVA the wrong approach without "fixed factors" or grouping variables?

Many thanks for you thoughts and/or advice. I hope my questions make sense.

Best wishes,

Anton