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I ran a MANOVA on 3 DVs against 2 IVs (2 levels each factor, so 2x2) and found no interaction effect, but I found a main effect for one of the IVs. Would it make sense to follow up with a discriminant analysis, especially since the univariate results were not significant?

EDIT to include research question: My 3 DVs are ratings on essay quality of 138 students. I want to know whether the presence or absence of one or both guidance tools (that are the two factors) significantly influences these ratings (control group receives no guidance). Since the univariate ANOVAs didn't yield any significance, I would like to know which of the 3 ratings (if any) are influenced more by the interventions.

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  • $\begingroup$ This is impossible to answer unless you explain what your research question is and what you are trying to prove or to investigate. $\endgroup$
    – amoeba
    Feb 10, 2017 at 14:56
  • $\begingroup$ @amoeba good point, I have just edited my post with the research question. Basically I would like to know which of the essay quality ratings was influenced by the intervention(s) the participants received (or didn't receive). $\endgroup$
    – iamnarra
    Feb 10, 2017 at 15:01
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    $\begingroup$ Yeah, sure, then follow up. See stats.stackexchange.com/questions/131241 and links therein. $\endgroup$
    – amoeba
    Feb 10, 2017 at 15:03
  • $\begingroup$ @amoeba great, I just needed to make sure since I have 2 IVs, so the discriminant analysis would only involve one IV that had a significant F value from MANOVA. $\endgroup$
    – iamnarra
    Feb 10, 2017 at 15:05
  • $\begingroup$ Conceptually it would be better to use both IVs. I don't know if this is possible with your software, but it is possible in principle, as I explain in the linked answer and in some answers that are linked from there. $\endgroup$
    – amoeba
    Feb 10, 2017 at 15:07

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