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I am using PROC PLS in SAS with multiple independent variables and multiple dependent variables. I would like to know how my independent variables are contributing to the scores for the first couple of generated components.

For example, if I was using principal components instead of partial least squares, I would look at the eigenvectors (principal component loadings) to determine this. Is there something similar I can look at for partial least squares? In the SAS documentation it refers to something called a "weight vector" that seems to be roughly what I want - but there does not appear to be any way of extracting it.

General suggestions for approaching this problem would also be appreciated!

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The weight vectors from PROC PLS can be extracted using the "details" option.

However, they are not particularly interpretable because they relate the components to the "deflated" X matrix, which changes after each component is computed. I found that using the SIMPLS method (done by specifying method=SIMPLS) gives me exactly what I want - variation in the dependent variables is accounted for when constructing the components, but the components are a linear combination of the original X matrix, and thus there are interpretable loading vectors to look at.

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