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thank you very much for your time! I am currently working on a neuroimaging study comparing lateralization indexes between the two hemispheres in three different groups. I have 4 lateralisation indexes (two different independent parameters for two different fiber tracts) and am now wondering whether it's better to use MANOVA or repeated-measures ANOVA. In the literature I found some studies looking for differences in diverse lateralization indexes via repeated measures ANOVA but I am not quite sure if this is the correct approach since the two indexes are independent and are not describing the same fiber tract.

Thank you very much for your help in this matter!

Marlene
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  • Take a look at this thread: [Differences between MANOVA and Repeated Measures ANOVA?](http://stats.stackexchange.com/questions/13197/differences-between-manova-and-repeated-measures-anova?rq=1), and also at [MANOVA vs. Repeated Measure ANOVA](http://stats.stackexchange.com/questions/45165/manova-vs-repeated-measure-anova?rq=1). Your question is very close to being a duplicate. – amoeba Feb 26 '14 at 14:39
  • But briefly: repeated measures ANOVA does *not* assume or suppose that your indices are "repeated measures of the same thing", which can be quite confusing. Having four indices that measure **different** things, but with each subject assessed with all four indices, does qualify for repeated measures ANOVA. The caveat is that for this test a *sphericity assumption* should hold. There are tests to check if it does. If it does not, you should either correct for it (which is messy), or use MANOVA. You can also choose to use MANOVA to be on the safe side (but pay the price of losing some power). – amoeba Feb 26 '14 at 14:57

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