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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