Dear all,
I am unsure about how to specify a model in R and I thought of asking
some advice to the list. I have two groups ("Group"= A, B) of
subjects, with each subject undertaking a test before and after a
certain treatment ("Time"= pre, post). Additionally, I want to enter
the age of the subject as a covariate (the performance on the test is
affected by age), and I also want to allow different slopes for the
effect of age in the two groups of subjects (age might affect the
performance of the two groups differentially).
Is the right model to use something like the following?
aov (y ~ Group*Time + Group*Age + Error(Subj/Group), data=df1 )
(If I enter that command, within summary, I get the following:
Error() model is singular in: aov(y ~ Group * Time + Group * Age +
Error(Subj/Group), data = df1))
As a second question: I have an outlier in one of the two groups.
The outlier is not due to a measurement error but simply to the
performance of the subject (possibly related to his medical history,
but I have no way to determine that with certainty). This subject is
signaled to be an outlier within its group: averaging the pre and
post values for the performance of the subjects in his group, the
Grubbs test yields a probability of 0.002 for the subject to be an
outlier (the subject is marked as a significant outlier also if I
perform the test separately on the pre and the post data).
If I remove this subject from its group, I get significant effects of
Group and Group X Age (not using the R formula above, but another
stat software), but if I leave the subject in those effects
disappear. Since I understand that removing outliers is always
worrysome, I would like to know if it is possible in R to estimate a
model similar to that outlined above but in a resistant/robust
fashion, and what would be the actual syntax to do that. I will very
much appreciate any help or suggestion about this.
thanks in advance and best regards
giuseppe
Giuseppe Pagnoni
Dept. of Psychiatry
101 Woodruff Circle
Altanta, GA 30322
Tel: 404-712-9582
Fax: 404-727-3233
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