Dear list member,
I deperately need an help in performing a MANOVA in R, but I encountered some
problems both in the design and in the synthax with R.
I conducted a listening experiment in which 16 participants had to rate the
audio
stimuli along 5 scales representing an emotion (sad, tender, neutral, happy and
aggressive).
Each audio stimulus was synthesized in order to represent a particular emotion.
Participants had to move 5 sliders each of which corresponded to one of the 5
emotions.
The sliders range was [0,10] but participants were only informed about the
extremities of
the sliders (not at all - very much). There was not a force choice, therefore
potentially each
audio stimulus could be rated with all the scales (e.g. sad = 0.1, tender = 2.5,
neutral = 2., happy = 8.3, aggressive = 1.7).
There were 40 stimuli, each stimulus was repeated twice, for a total of 80
trials.
I want to demonstrate that the created stimuli were actually correctly
classified in the
corresponding emotion. For example I expect that happy sounds result in happy
ratings
by participants and that these happy ratings are greater than the other 4
responses.
To analyze the data I want to use a MANOVA with repeated measures. For this
purpose
I would like to use the audio stimulus as independent variable having 40 levels,
while
the 5 responses as dependent variables. Since each individual has been measured
twice,
I include a within-subjects factor for trial number.
However, with 40 levels I would have 39 degrees of freedom, that with only 16
participants is not appropriate. For this reason I have also grouped the audio
stimuli
by their type. So my independent variable could be Trial_type, having 20 levels.
Unfortunately, reducing in this way is still too few for 16 participants.
Therefore my idea is to perform a MANOVA not on the whole table, but separately
for each subset defining an emotion. In this way I would have just 4 lvels.
My question is: is this a correct approach to analyze data?
Or it is better to use other strategies?
For example, looking at the following .csv table which can be downloaded here:
https://dl.dropbox.com/u/3288659/Results_data_listening_Test_Grouped.csv
I create the subset for emotion Sad, and then I try to perform the MANOVA with
repeated measures on it:
Sad <- subset(scrd, Emotion == "Sad")
model.emotions<-lm(cbind(Sad,Tender,Neutral,Happy,Aggressive) ~
Trial_type,data=scrd)
idata<-data.frame(scrd$Trial_number)
aov.emotions<-anova(model.emotions,idata=idata, idesign=~ Trial_type,
type="III")
Unfortunately I get the following error which I am not able to solve:
> aov.emotions<-anova(model.emotions,idata=idata, idesign=~Trial,
type="III")
Error in cbind(M, X) : number of rows of matrices must match (see arg 2)
I am not fully sure of the above code, since I am not an expert in R. Can you
please correct them
showing the correct R code?
To the experiment was performed by two groups of listeners: musicians and
non-musicians. I created
two plots of the results, on for the groups of musicians and the other for the
group of non-musicians:
https://dl.dropbox.com/u/3288659/exp2_musicians.pdf
https://dl.dropbox.com/u/3288659/exp2_non_musicians.pdf
Finally, I was not able to find any post hoc test to apply to the result of the
MANOVA in case of
a significant main effect. Any suggestion?
Thanks in advance
Best regards
Angelo
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