R help - Feb 2011 - Analyzing dissimilarity ratings with Multidimensional Scaling

Dear R-list members,
I need an help with the Multidimensional Scaling analysis (MDS).
So far I used the cmdscale() command in R, but I did not get the perceptual
map I would love to see,
and I would like to know if it is possible to get it using R, and if yes
how.
I also had a look to the functions isoMDS() and sammoc() but with no luck.

I summarize the experiment I performed, and I would ask you an help to show
me how
to analyze in R my results.

I simulated 6 surfaces materials at auditory and visual level, and I asked
subjects to evaluate on a 9-point Likert scale the degree of coherence
between
the two stimuli. For example, there are trials where at auditory level a
metal
surface was simulated and at visual level the snow surface, or wood both at
auditory and visual level.

The experiment had only 12 participants, so for each trial I have 12
response
(no repeated measures involved).
In total there were 36 trials (the combinations of the 6 materials), and
each trial was
evaluated only once by each of the 12 participants.


Basically, these are my data:

     WD   MT   SW   GR   SN   DL
WD 7.00 6.50 4.91 4.83 5.50 5.00
MT 7.33 6.91 2.08 3.16 4.25 3.25
SW 2.91 1.75 7.91 6.25 6.83 5.41
GR 2.91 2.66 6.25 6.41 7.25 6.75
SN 4.00 4.00 5.58 6.00 7.00 6.58
DL 3.91 3.08 5.16 6.25 6.50 6.83

On the rows there are the visual stimuli and on the columns the auditory
stimuli. In each
cell there is the average score for each trial (e.g. the trial GR-MT is
2.66, that
is the average score given by participants to the trial where the material
"gravel"
was provided at visual level and the material "metal" was provided ar
auditory level).


My first goal in the analysis process is to print a perceptual map where to
place the pairs of
audio-visual stimuli (e.g. WD-WD, MT-DL, etc.) and see how far the trials
are from each other.
I used cmdscale in R but I did not get the wanted result. Any suggestion?

My second goal would be to find some p-values assessing the significant
statistical differences.

For example I would like to understand if having the coherent couple of
stimuli
SW-SW (which means "snow" both at auditory and visual level) produces
significant
differences in the evaluations rather than the couple SW-MT (which means
"snow"
at auditory level and "metal" at visual level)

Again, I would like to undestand if there is any significant difference
between
all the couples of stimuli corresponding to solid surfaces (like the couples
MT-MT,
MT-WD, WD-WD, MT-MT) and all the couples where a solid surface and a
aggregate surface
are presented (like the couples MT-SN, or WD-GR, etc.).


I really thanks anyone who can provide any suggestion or useful information.
I extensively searched in the R list mailing list topics but I did not find
anything
that could fit my case.

Thanks in advance

Kind regards


Luca
-- 
---------------------------------------------------------------

"Music is a moral law:
It gives a soul to the Universe,
wings to the mind,
flight to the imagination,
a charm to sadness,
and life to everything.
It is the essence of order,
and leads to all that is good,
just and beautiful,
of which it is the invisible,
but nevertheless dazzling,
passionate, and eternal form".

Plato, 400 B.C. (from the Dialogues)

	[[alternative HTML version deleted]]

> My first goal in the analysis process is to print a perceptual map where to
> place the pairs of
> audio-visual stimuli (e.g. WD-WD, MT-DL, etc.) and see how far the trials
> are from each other.
I've been using heatmap for stuff like this.
You can get a nice picture this way and get quick visual
survey and dendrograms, 

xm<-scan(file="avm.txt")
str(xm)
heatmap(xm)
heatmap(matrix(xm,6,6))

I ran the above on your data and it visually looks
like there could be interesting patterns to test.