If this does NOT answer your question, PLEASE do read the posting
guide! (www.R-project.org/posting-guide.html) and send us another post.
Realize, however, that in r-help as in just about any other aspect of
human existence, people who are more clear about what they want are
generally more successful.
3. I used MANOVA on a project 30 years ago. From that and
subsequent experience, it seem to me that MANOVA is a highly specialized
tool for which the required assumptions are rarely met. Most people are
much better off making lots of plots to possible models and then
residuals from model fits, etc. In rare cases, MANOVA doubtless can
find effects that can not be seen in the component univariate analyses.
However, I have yet to encounter such a case. If I had time to pursue
a modeling effort beyond simple univeriate analyses, I thing I would
move to "structural equation modeling" (package sem) or "partial least
squares". "RSiteSearch" can lead you to R capabilities for these. (See
hope this helps.
> Hi all,
> I am experimenting the function "manova" in R.
> I tried it on a few data sets, but I did not understand the result:
> I used "summary(manova_result)"
> and "summary(manova_result, test='Wilks')"
> and they gave a bunch of numbers...
> But I need the Sum-of-Squares of BETWEEN and WITHIN matrices...
> How do I read off from the R's manova results?
> Any good example code and results?
> Also, I am looking for tutorials/notes on how to compute those BETWEEN and
> WITHIN Sum-of-Squares myself...
> I did not find any good discussion about MANOVA on the quite a few books I
> have on my hand currently...
> Any books/referecnes/notes/tutorials give clear formulas on how to compute
> the MANOVAs?
> Thanks a lot!
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> https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: MANOVA: how do I read off within and between Sum-of-Squares info from the manova result?
> However, I have yet to encounter such a case. If I had time to pursue
> a modeling effort beyond simple univeriate analyses, I thing I would
> move to "structural equation modeling" (package sem) or "partial least
> squares". "RSiteSearch" can lead you to R capabilities for these. (See
> also "http://finzi.psych.upenn.edu/R/Rhelp02a/archive/29119.html").
Another option is to look at your data in their original high
dimensional space, eg., with the grand tour in GGobi
(http://www.ggobi.org, http://ggobi.org/demos/tour.html). MANOVA
tests the hypothesis that the means are different (assuming
multivariate normality and a common variance-covariance matrix). By
looking at your data you can investigate more interesting hypotheses -
are the groups overlapping? is there a linear or non-linear separation
between the groups? are the responses highly correlated?