Study:
I simulated some surfaces materials at audio and haptic 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 stimuli with metal at auditory level and snow at haptic level, or wood both at auditory and haptic level.
So it is like a dissimilarity rating experiment.
The experiment had only 12 participants, so for each stimulus I have 12 response (no repeated measures involved).
Question:
How should I analyse the following experiment?
Initial Thoughts:
So far the only way I am thinking to use is ANOVA.
Update
Hello again, I used the cmdscale command in R, but I did not get thecperceptual map I would love to see. I as you an help! Maybe the problem is that I misunderstood if my table is well built for the purpose of the analsys.
Let´s summarize my experiment, my goals and the problem:
I simulated some surfaces materials at audio and haptic 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 haptic level the snow surface, or wood both at auditory and haptic 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, and each trial was evaluated only once by each of the 12 participants. So each subject provided 36 ratings on the 9 point Likert scale, one for each trial.
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 the haptic 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 haptic level and the material "metal" was provided ar auditory level).
Now I want to analyze the data in the correct ways, and as said MDS is the best analysis instead of ANOVA as I was thinking.
My first goal is to print a perceptual map where to place the pairs of audio-haptic stimuli (e.g. WD-WD, MT-DL, etc.) and see how far are the trials 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 like I normally get with ANOVA.
For example I would like to understand if having the coherent couple of stimuli SW-SW (which means "snow" both at audio and haptic level) produces significant differences n the evaluations rather than the couple SW-MT (which means "snow" at audio and "metal" at haptic level)
Again I would like to undestand if there is any statistical 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 want to get as many information as possible from that table. I really thanks anyone who can provide any suggestion or useful information.