  

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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