1. You did NOT provide an example, so I don't know if the following

example will help. I got it by following ?manova to "?summary.manova".

tear <- c(6.5, 6.2, 5.8, 6.5, 6.5, 6.9, 7.2, 6.9, 6.1, 6.3,

6.7, 6.6, 7.2, 7.1, 6.8, 7.1, 7.0, 7.2, 7.5, 7.6)

gloss <- c(9.5, 9.9, 9.6, 9.6, 9.2, 9.1, 10.0, 9.9, 9.5, 9.4,

9.1, 9.3, 8.3, 8.4, 8.5, 9.2, 8.8, 9.7, 10.1, 9.2)

opacity <- c(4.4, 6.4, 3.0, 4.1, 0.8, 5.7, 2.0, 3.9, 1.9, 5.7,

2.8, 4.1, 3.8, 1.6, 3.4, 8.4, 5.2, 6.9, 2.7, 1.9)

Y <- cbind(tear, gloss, opacity)

rate <- factor(gl(2,10), labels=c("Low", "High"))

additive <- factor(gl(2, 5, len=20), labels=c("Low", "High"))

fit <- manova(Y ~ rate * additive)

summary.aov(fit) # univariate ANOVA tables

summary(fit, test="Wilks") # ANOVA table of Wilks' lambda

2. To proceed further, I tried the following:

> class(fit)

[1] "manova" "maov" "aov" "mlm" "lm"

Inspired by this, I then tried the following:

> ?methods

> methods(class="manova")

[1] summary.manova

> methods(class="maov")

no methods were found

> methods(class="mlm")

[1] add1.mlm* anova.mlm deviance.mlm* drop1.mlm*

[5] estVar.mlm* mauchly.test.mlm* plot.mlm predict.mlm

[9] SSD.mlm* summary.mlm vcov.mlm*

Non-visible functions are asterisked

This led me further:

> fit

Call:

manova(Y ~ rate * additive)

Terms:

rate additive rate:additive Residuals

tear 1.7405 0.7605 0.0005 1.7640

gloss 1.3005 0.6125 0.5445 2.6280

opacity 0.4205 4.9005 3.9605 64.9240

Deg. of Freedom 1 1 1 16

Residual standard error: 0.3320392 0.4052777 2.014386

Estimated effects may be unbalanced

> estVar(fit)

tear gloss opacity

tear 0.110250 0.00125 -0.191875

gloss 0.001250 0.16425 -0.034500

opacity -0.191875 -0.03450 4.057750

> SSD(fit)

$SSD

tear gloss opacity

tear 1.764 0.020 -3.070

gloss 0.020 2.628 -0.552

opacity -3.070 -0.552 64.924

$call

manova(Y ~ rate * additive)

$df

[1] 16

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

also "

http://finzi.psych.upenn.edu/R/Rhelp02a/archive/29119.html").

hope this helps.

spencer graves

Michael wrote:

> 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!

>

> [[alternative HTML version deleted]]

>

> ______________________________________________

>

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