Hi all, So I think I have seen some similar questions to mine when I searched the archives, but have not seen any concrete answers and was wondering if any one could help. I have been trying to use R's aov() function to analyze my data. I have a 3 x 4 x 2 repeated measures design. All of the IVs are within subjects. I do also have missing values (unequal N), as I have to remove any incorrect trials for each subject.
Here is the code I entered and the error message: a<-aov(log(rt)~(tran*block*half) + Error (sid/ (tran*block*half)), data=mydata2) Warning message: Error() model is singular in: aov(log(rt) ~ (tran * block * half) + Error(sid/(tran * block * I then do summary(a) and am able to get an output, but I am not sure whether or not I can trust that output since I got the error message. Any body have any thoughts/solutions for this? Also, are there any benefits of you aov() vs. use some of the linear model functions or vice versa? Thanks for any help you can offer!! ~Leigh Alexander ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
