I am designing my study, but I am a little stuck in which test I eventually should use. I have a between-subject design with 6 conditions (let's say A, B, C, D, E, F), with each having 6 responses (let's call these a, b, c, d, e, f), on a 7-point scale:
IV (condition) -> DV A -> a, b, c, d, e, f B -> a, b, c, d, e, f C -> a, b, c, d, e, f D -> a, b, c, d, e, f E -> a, b, c, d, e, f F -> a, b, c, d, e, f
So, each condition has 6 dependent variables. I don't want to test difference between the conditions, but only the effect of the condition on the different DV's. For example, when someone is in condition A, I would expect them to score higher on DV a than on DV b, c, d, e, and f. When someone is in condition B, I would expect them to score higher on another DV, and so forth.
Later on, I expect also some moderator effects, but I guess that's only adding interaction terms to the model.
Can I use separate tests for each condition? Or should I test it in one big model? What kind of test would be most suitable for this. Most tables that should help you choose a statistical test only show options with 1 DV.