Hi, 
 
I haven't recieved any replies to my last email, so let me be a bit more
specific. I have a dataframe and it has the following structure:
 
                                Condition
Mapping     Subject        A        B        C
1            1             5        10       15 
1            2
1            3
1            4
1            5
1            6
1            7
1            8
2            9
2            10
 
Mapping is a between-subject factor. Condition is a within-subject factor.
There are 5 levels of mapping, 8 subjects nested in each level of mapping.
For each of the 40 combinations of mapping and subject there are 3
observations, one in each level of the condition factor. 
 
I want to estimate the pooled error associated with the following set of 4
orthogonal contrasts:
 
condition.L:mapping.L
condition.L:mapping.Q
condition.L:mapping.C
condition.L:mapping^4
 
What is the best way to do this? One way is to estimate the linear contrast
for condition for each subject, create a 40 row matrix where the measure for
each combination of mapping and subject is the linear contrast on condition.
If I pass this dataframe to aov, the mse it returns is the value I am
looking for. 
 
If possible, I would like to obtain the estimate without collapsing the
dataframe, but am not sure how to proceed. Suggestions?
 
Steve

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