Hi all
I've recently grasped the concept of nested factors, which should allow
me to delve further into the subtleties of the data I'm studying.
Previously I had recognized that there would be a problem with the
assumptions of independence for comparing measurements of things nested
within common factors, and I dealt with it by averaging everything
(probe intensities within probe sets within chip replicates in my case)
that couldn't be shown to be independent. Anyway, I've figured out (I
think) how Stata deals with nesting factors, and simultaneously
discovered that it __really__ increases the processing demand on the
system! I've had to blow up my matsize from the default 400 to 4800,
and it's taking a lot longer to get results from a 4000 observation, 7
factor ANOVA. Two questions:
1. Is this to be expected, or am I still not describing something
properly in my ANOVA statement to Stata?
2. What's happening behind the scene that causes the matsize inflation
and bogging of processing speed?
For your amusement, here's the ANOVA statement:
anova logcpint benchdwellmin hyb nMES ///
die / die|unit / die|unit|atom ///
benchdwellmin*nMES ///
,continuous(benchdwellmin) partial regress anova
I split it up across lines like that to help account for the factors,
nesting levels, and interactions I'm trying to observe.
John Wallace | Research Associate | Test Method Development
AFFYMETRIX, INC. | 3380 Central Expressway | Santa Clara, CA 95051 |
Tel: 408-731-5574 | Fax: 408-481-0435
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