[R] ss's are incorrect from aov with multiple factors (EXAMPLE!)
jc at or.psychology.dal.ca
Sun Jul 13 00:47:32 CEST 2003
On Saturday, July 12, 2003, at 07:40 AM, Peter Dalgaard BSA wrote:
> factor, and no, you should not expect otherwise. The various SS in the
> full analysis are distance measures in 24-dim space, whereas in the
> aggregated analysis you get a distance in 12-space. The relation is
> that every value entering in the b and s:b terms will be duplicated in
> the former, hence the SS is twice as big.
> This is standard procedure, and R does the same as e.g. Genstat in
> this respect. It is also necessary to ensure that the residual MS are
> comparable, e.g. that you can test for a significant s:b random effect
> by comparing with the residual MS to that of the s:a:b stratum.
OK, perhaps I need a little help then. Suppose I do an interaction
plot of a*b and I want to see what it looks like with 95%CI error bars.
Following Loftus & Masson (1995) there would be one of two ways. I
could generate an error bar for the main effect I was interested in and
stress in the description that the error bars only apply across that
main effect. I take it from what you have said that I would collapse
the data in order to generate a proper error bar for only one effect.
Or, I could generate one from a weighted average of the MSE from a, b,
and a:b. The question I have is, would I get each of the main effects
in that from separate analyses?
BTW, Statview seems to generate the same MSE for me whether I collapse
the data or not.
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