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Date:         Wed, 12 Mar 2003 10:54:21 -0800
Reply-To:     cassell.david@EPAMAIL.EPA.GOV
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         "David L. Cassell" <cassell.david@EPAMAIL.EPA.GOV>
Subject:      Re: Non Sign. Main Effect/Significant Post Hoc
Content-type: text/plain; charset=us-ascii

Thompson Bill T Contr USAFSAM/FEC <Bill.Thompson@BROOKS.AF.MIL> wrote: > In writing the code for performing a MANOVA I included the code for > performing post hoc tests on the main effects before knowing if they were > significant. Interestingly the results showed no main effect for my > variable but when looking at the bonferroni (only 3 levels of indep. var.) > post hoc it showed significance. Even more interesting is that in another > analysis the exact opposite occurred where there was a significant main > effect but post hoc analysis did not identify a significant relationship.

I second everything Jim Groeneveld said. You cannot expect that the overall F test and individual values of multiple comparison tests will give you the same answer, *particularly* when using something like Bonferroni. In fact, I don't recommend using Bonferroni here. I would recommend Tukey, without knowing more of your analysis plan.

If your data do not meet the underlying assumptions of your MANOVA, then you can get really differing results. In particular, if you have unequal variances, then individual pairwise comparisons may look quite unlike one overall test assuming homoskedasticity. As Jim alluded, consider plotting out your data to see: (1) if your assumptions are being met; (2) if your data really look like some levels have differing means than other levels; and (3) if there might be other effects or interactions driving some of your process.

HTH, David -- David Cassell, CSC Senior computing specialist mathematical statistician

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